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With the increasing adoption of fifth-generation (5G) networks and wide bandwidth availability, unmanned aerial vehicles (UAVs) should now be practicable to stream and operate at different altitudes and upload incredibly large quantities of data from sensors. We develop a novel intelligent sensing framework (Choi, 2020) so that sensing and communication occur on demand, according to a given query. Our query-based Data Aided Sensing (DAS) approach differs from existing methods as we start with selecting relevant nodes based on the query and then allocating UAVs for collecting measurements. We develop an economical and efficient approach to collect measurements from massive passive sensors, which adaptively minimize the entropy gap while scheduling UAVs to sensors. At the heart of our solution is a mathematical approach for estimating entropy, cost and energy consumption, thereby deploying dynamically optimal UAV-sensor association (e.g., optimizing entropy and employing bipartite graph). Our system has been evaluated with extensive simulations, providing insightful observations and findings.

In this paper, we study data-aided sensing (DAS) for distributed detection in wireless sensor networks (WSNs) when sensors' measurements are correlated. In particular, we derive a node selection criterion based on the J-divergence in DAS for reliable decision subject to a decision delay constraint. Based on the proposed J-divergence based DAS, the nodes can be selected to rapidly increase the log-likelihood ratio (LLR), which leads to a reliable decision with a smaller number of the sensors that upload measurements for a shorter decision delay. From simulation results, it is confirmed that the J-divergence based DAS can provide a reliable decision with a smaller number of sensors compared to other approaches., 5 pages, 3 figures, to appear in IEEE Wireless Communications Letters

Security constraint is a key component in unit commitment to guarantee reliable generator commitment. Large set of security constraints are notorious for making the problem difficult to solve. Constraint screening, i.e., filtering out non-dominating constraints, is regarded as a powerful tool to address this challenge. This work presents a security-constraint screening that can effectively integrate virtual transaction and capture changes online in real-time or look-ahead markets. The proposed approach takes advantage of both deterministic and statistical methods, which leverages mathematical modeling and historical data. Effectiveness are verified using Midcontinent Independent System Operator (MISO) data.

Urbanizationis accompanied by rapid social and economic development, while the process of urbanization causes the degradation of the natural ecology. Direct loss in vegetation biomass from areas with a high probability of urban expansion can contribute to the total emissions from tropical deforestation and land-use change. Monitoring of urban expansion is essential for more efficient urban planning, protecting the ecosystem and the environment. In this paper, we use remote sensing data aided by Google Earth Engine (GEE) to evaluate the urban expansion of the city of Isfahan in the last thirty years. Thus, in this paper we use Landsat satellite images from 1986 and 2019, integrated into GEE, implementing Support vector machine (SVM) classification method. The accuracy assessment for the classified images showed high accuracy (95-96%), while the results showed a significant increase in the urban area of the city of Isfahan, occupying more than 70% of the study area. For future studies, we recommend a more detailed investigation about the city expansion and the negative impacts that may occur due to urban expansion.

The Quadrilátero Ferrífero region, located in the southeast portion of the São Francisco Craton, is one of the main metallogenic provinces in Brazil. Fieldwork, petrography, high-resolution airborne geophysics (magnetic and gamma-ray spectrometry data), and aerial images allowed us to produce a new map at the 1:25,000 scale, with important contributions in the lithotypes detailing, understanding of the geological structures and relationship between the different stratigraphic units. Interpretation of airborne geophysical data integrated with field structural and lithological observations were successfully employed in the creation of the litho-structural framework in a poorly exposed Proterozoic and Archean terrain. Airborne gamma-ray spectrometry data aided in the mapping process in areas with regolith cover including erosional ridges. The magnetic total derivative image revealed regional and local structures. In addition, our work details the units of occurrence of Rio das Velhas and Minas Supergroup. The aerial coverage of the Mindá and Santa Quitéria formations strongly increased, as well as the area of the Cauê Formation was better defined. The new geological map provides many improvements over the pre-existing maps. New lithological facies and structures were identified and others become more visible and lithologicalboundaries are refined or confirmed.

In order to ensure the performance of burst signal demodulation, forward symbol timing offset estimation algorithm is usually used for symbol timing recovery. Aiming at the shortcomings of common forward symbol timing estimation algorithms, a new algorithm based on maximum likelihood estimation joint trigonometric polynomial interpolation is proposed in this article, which is suitable for the data of four samples per symbol and can resist large frequency offset. Hereafter, in order to make it more suitable for engineering practice, optimize it into an improved data-aided (DA) forward symbol timing offset estimation algorithm with multiple characteristics, e.g., moderate frequency offset capture range, insensitive to shaping coefficient, relatively low complexity, excellent estimation performance, flexible algorithm structure and less sample data required for calculation. The simulation results show that the performance of the improved algorithm in this article can approach the modified cramer-rao bound (MCRB) within the frequency offset capture range, under the conditions of low signal to noise ratio (SNR) and small shaping coefficient.

Digital communication has proven to be the most efficient method of data transmission especially where long distances are involved. This led to the invention of more sophisticated methods of communication ranging from mobile handset communication to more advanced satellite communication. The speeds of passing information have been improving over the years and real time video communication has been made possible with digital devices. Various methods of digital data transmission are employed based on the information to be transmitted. This paper focuses on carrier recovery in digital communication systems, especially those based on Quadrature Phase Shift Keying (QPSK) modulation and demodulation scheme. The design being implemented is that of coherent demodulation for QPSK scheme using SIMULINK design tool. Performance of QPSK is also investigated to make a comparison and the suitability of the scheme to use in digital data transmission applications.

Geographical origin and authenticity are the two crucial factors that propel overall cheese perception in terms of quality and price; therefore, they are of great importance to consumers and commercial cheese producers. Herein, we demonstrate a rapid, accurate method for discrimination of domestic and import mozzarella cheeses in the Republic of Korea by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The protein profiles’ data aided by multivariate statistical analysis successfully differentiated farmstead and import mozzarella cheeses according to their geographical location of origin. A similar investigation within domestic samples (farmsteads/companies) also showed clear discrimination regarding the producer. Using the biomarker discovery tool, we identified seven distinct proteins, of which two (m/z 7407.8 and 11,416.6) were specific in farmstead cheeses, acting as potential markers to ensure authentication and traceability. The outcome of this study can be a good resource in building a database for Korean domestic cheeses. This study also emphasizes the combined utility of MALDI-TOF MS and multivariate analysis in preventing fraudulent practices, thereby ensuring market protection for Korean farmstead cheeses.

To better study hip and knee replacement, 50 eligible hip and knee patients from March 2020 to April 2021 were selected. A 1 : 1 scale solid model was printed with CT thin-layer scanning data assisted by 3D printing technology to evaluate the ankle function of patients six months after surgery. The results showed that the 3D rapid prototyping time of the 1 : 1 fracture model in 50 patients was 3-4 hours. The operation time was 70–90 min, and the average operation time was 80 min. The actual application in operation was consistent with that in the simulation of the 3D printing model, after surgery, and there was no infection of incision soft tissue or loss of reduction in all 50 patients. CT thin-layer scan data aided 3D printing technology can help clinical hip and knee replacement simulation and planning, improving surgery’s accuracy and safety.

Parental relatedness of present-day humans varies substantially across the globe, but little is known about the past. Here we analyze ancient DNA, leveraging that parental relatedness leaves genomic traces in the form of runs of homozygosity. We present an approach to identify such runs in low-coverage ancient DNA data aided by haplotype information from a modern phased reference panel. Simulation and experiments show that this method robustly detects runs of homozygosity longer than 4 centimorgan for ancient individuals with at least 0.3 × coverage. Analyzing genomic data from 1,785 ancient humans who lived in the last 45,000 years, we detect low rates of first cousin or closer unions across most ancient populations. Moreover, we find a marked decay in background parental relatedness co-occurring with or shortly after the advent of sedentary agriculture. We observe this signal, likely linked to increasing local population sizes, across several geographic transects worldwide., Little is known about how human parental relatedness varied across ancient populations. Runs of homozygosity (ROH) in the offspring’s genome can give clues. Here, the authors present a method to identify ROH in ancient genomes and infer low rates of close kin unions across most ancient populations.

International audience; In this paper, we calculate the Cramer-Rao bound (CRB) for single side band continuous phase modulation signals (SSB-FSK). The CRB is useful to design an optimum preamble sequence to jointly estimate the frequency offset, symbol timing, and carrier phase. The goal is to find preamble sequences that minimize the CRBs of all estimated parameters. The results provide some useful preambles, which can be added to data packets for synchronization in burst-mode SSB-FSK transmissions. © 2020 URSI.

Since there are a number of Internet-of-Things (IoT) applications that need to collect data sets from a large number of sensors or devices in real-time, sensing and communication need to be integrated for efficient uploading from devices. In this paper, we introduce the notion of data-aided sensing (DAS) where a base station (BS) utilizes a subset of data that is already uploaded and available to select the next device for efficient data collection or sensing. Thus, using DAS, certain tasks in IoT applications, including federated learning, can be completed by uploading from a small number of selected devices. Two different types of DAS are considered: one is centralized DAS and the other is distributed DAS. In centralized DAS, the BS decides the uploading order, while each device can decide when to upload its own local data set among multiple uploading rounds in distributed DAS. In distributed DAS, random access is employed where the access probability of each device is decided according to its local measurement for efficient uploading., Comment: 6 pages, IEEE WCNC 2020

The development of GNSS (Global Navigation Satellite System) and LEO (Low Earth Orbiting) satellites missions enhanced new possibilities of the terrestrial atmosphere probing. The Radio Occultation (RO) technique can be used to retrieve profiles from the neutral and the ionized atmosphere. An important advantage of using RO data is the spatial distribution, which enables global coverage. The signal transmitted by GNSS satellites and tracked by receivers embedded at the LEO satellites is influenced by the atmosphere which causes signal refraction. Due to the signal and atmospheric interaction, instead of a straight line, the signal propagates as a curved line in the path between the transmitter and receiver. The satellites geometry allows the retrieval of atmospheric refractive index, which carries several characteristics from its composition, such as pressure and temperature of the neutral atmosphere, and electron density of the ionosphere. In 1995 GPS/MET (Global Positioning System/Meteorology) experiment was launched to prove the RO concept and, since then, several LEO missions with GNSS receiver embedded were developed, such as CHAMP (Challenging Mini-satellite Payload) (2001-2008), SAC-C (Satélite de Aplicaciones Cientificas-C) (2001-2013) and COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) (2006-present). COSMIC is one of the RO missions with the greatest amount of atmospheric data available, mainly taking into account ionospheric information. In the RO technique, in general, the Abel retrieval is used to retrieve the refractive index. The Abel retrieval assumes a spherical symmetry of the atmosphere. When considering the electron density profiles, the main issue is related to regions with large horizontal gradients, where the spherical assumption presents the biggest degradation. In order to improve the ionospheric horizontal gradient used to retrieve electron density profiles, many researches have performed experiments using data from different sources. In this paper, we aimed to assess the electron density profiles over the Brazilian area (equatorial region), characterized by intense ionospheric variability, considering RO data and Global Ionospheric Maps (GIM). The data used is from COSMIC mission, in a period close to the last solar cycle peak (2013-2014). Ionosonde data were used as reference values to assess the RO with GIM aided data. Total Electron Content (TEC) data from GIM were used to estimate the variability of ionosphere between the ionosonde position and the profile locations. This research builds on a preliminary investigation related to the assessment of RO ionospheric profiles over a region under intense ionospheric variability, such as the Brazilian territory. Future works may take into consideration the use of other ionospheric information such as regional ionospheric maps, with higher resolution, and ionospheric tomography.

In this paper, we propose a new algorithm of iterative least squared (LS) channel estimation for 64 antennas Massive Multiple Input, Multiple Output (MIMO) turbo-receiver. The algorithm employs log-likelihood ratios (LLR) of low-density parity-check (LDPC) decoder and minimum mean square error (MMSE) estimator to achieve soft data symbols. These soft data symbols are further MMSE-weighted again and combined with pilot symbols to achieve a modified LS channel estimate. The modified LS estimate is employed by the same channel estimation unit to enhance turbo-receiver performance via channel re-estimation, as a result, the proposed approach has low complexity and fits any channel estimation solution, which is quite valuable in practice. We analyze both hard and soft algorithm versions and present simulation results of 5G turbo-receiver in the 3D-UMa model of the QuaDRiGa 2.0 channel. Simulation results demonstrate up to 0.3dB performance gain compared to the unweighted hard data symbols utilization in the LS channel re-calculation., Comment: Accepted for presentation at the VTC2020-Spring conference

The behaviour of rock mass is governed by the properties of the intact rock, the joints and the water conditions. Moreover, this behaviour is also influenced by the temporal and spatial damage evolution patterns of the rock. Thus, in this study, an approach that couples joints, water and microseismicity is proposed to model rock engineering problems. Joints are used to reduce the global properties of the rock mass, water is used to reduce the local properties of the rock mass, and microseismicity are used to reduce the point properties of the rock mass. Using data from the Shirengou iron mine, the effects of water and joints on the properties of rock masses were investigated, and a representative elementary volume of rock mass was determined. Then, a coupled fluid–solid numerical model was established to simulate the evolution of rock mass damage while considering the effects of joints and water. Finally, an inversion model of rock damage based on microseismic moment tensor was proposed. A numerical simulation of rock mass damage that couples joints, water and microseismicity was performed. The rock mass damage mechanism was then analysed. Joints and water were found to significantly affect the damage zones. The rock mass damage estimate would not be accurate without considering the effects of joints and water. Thus, water was the critical factor in the studied damage pattern. Further integration of microseismic data aided in modifying the numerical results and in predicting the damage development. The proposed approach can efficiently assess rock mass damage evolution and provide a basis for rock support.

Security constraints are necessary in unit commitment problems to guarantee reliable commitments. However, only a small subset of security constraints can bind in the unit commitment problem. This paper presents a data-aided prescreening approach that could identify and remove non-dominating security constraints. This approach takes advantage of both deterministic and statistical methods, which leverages the historical data and linear programming (LP) solution. Lazy constraints are used in optimization solver to maintain solution integrity. Case studies presented here use Midcontinent Independent System Operator (MISO) data, and simulation results show that the proposed prescreening approach significantly improves computational performance.

In this paper the study of the thermodynamic performance for a 6kW micro gas turbine power plant has been optimized by considering Air-fuel ratio at various altitudes along with fuel inlet temperature. The parametric analysis was performed to improve the overall efficiency of the power plant to obtain the required power needed by a multi-copter. The research deals with parametric optimization for determining realistic and practical combinations for improving the specific fuel consumption and overall efficiency of the Micro gas turbine power plant. The use of recuperators has not been beneficial for the micro gas turbine power system due to the increase in the total volume and weight of the engine. The fuel inventory should be decreased significantly to justify the addition of a recuperator system. The addition of heat exchangers improves the Specific fuel consumption that results in environmental friendly micro gas turbine engines. The result of this work helps to develop and design the micro gas turbine with high efficiency and at the optimized output. A model for a 6 kW micro gas turbine power plant was optimized for the application of primary power units for multi-copter or drones at low altitude conditions. To validate the model, JET CAT PHT3 shaft turbine design parameters were used and the results are compared with the experimental tests on this engine.

Efficient chemical application is a critical operation during specialty crop production that requires constant sprayer calibrations as well as pertinent adjustments to avoid off target spray losses. However, lack of rapid and in-field assessment tools limit the opportunities for frequent adjustments of orchard sprayer attributes. To overcome such limitations, our team has developed a smart spray analytical system (SSAS). Using SSAS, this study evaluated two commercial orchard sprayers, S1 (Powerblast 400, Rears Manufacturing Co., Eugene, OR, USA) and S2 (Turbo-Mist S30P300NSHD, Slimline Manufacturing Ltd., Penticton, BC, Canada), for their air-assist velocity and spray delivery patterns. Air-assist velocity patterns were studied in controlled conditions along two major planes: along the sprayer air-outlet (P1) and parallel to an imaginary tree row wall (P2), representing specific distances from the sprayer to tree row middles. SSAS data aided in generating several 2-D contour plots of the air-assist velocities along both the planes and for both sides of selected sprayers. Spray delivery patterns were generated along the typical locations of tree row wall and were based on pertinent air-assist velocity patterns. Results suggested that the magnitude of air-assist velocities was higher on the right side for sprayer S1 and on left side for sprayer S2. Such differences could be attributed to the design of fans, blades, rotation, air-inlet and outlet. There existed a consistent shift in air-assist along P2 plane and hence the spray delivery pattern shift on either side of both the sprayers. The uniformity in air-assist velocities decreased with the increasing distance from sprayer outlet. Average symmetries of 82.02 ± 12.81 (standard deviation) % and 44.27 ± 11.44% were observed in air-assist patterns for sprayer S1 and S2 along the plane P1, respectively. Similarly, average symmetries of 87.67 ± 0.53% and 74.03 ± 1.56% were observed in spray delivery patterns for sprayer S1 and S2, respectively. Overall, SSAS was consistent in quantification of the air-assist velocities (standard error ≤ 0.45 m s−1) and spray delivery patterns (standard error ≤ 0.07 ml cm−2) of commercial orchard sprayers and can be used at manufacturing stage for building consistent units as well as in the orchard settings for adjusting sprayer attributes to achieve targeted delivery on to the crop canopies.

The development of small & medium enterprises (SMEs) is a vital factor for Sri Lanka as SMEs currently contribute to 52 % of the GDP. The growth of SMEs in Sri Lanka is mainly affected by the technology related problems such as, lack of customized machinery providers, limited resource availability for technological consultancy, lack of technical skill development programs and access to information. This research aims to investigate the opportunity of promoting the University-Industry collaboration as an influential tool to address the technological problems of SMEs by means of utilizing the research and innovative capabilities of universities. The data for the study were collected through review of previous literature, questionnaires, semi-structured interviews with SMEs & Industrial Development Board. Qualitative and quantitative analysis of this data aided authors to recognize the technological needs of SMEs that can be fulfilled through the university participation. Furthermore, this relationship will benefit both the parties to have a mutual gain where the knowledge and skills of universities are practically used in industrial applications and SMEs will receive technological support. Also, it was identified that, the application of entrepreneurial university concept can further strengthen this relationship in future, where an entrepreneur can be erected from a university background who can act as the technology transfer intermediator between SMEs and universities.

This paper is concerned with the channel estimation for orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) systems in the presence of time varying channels. Although the estimation of the channel state information (CSI) for OFDM-IDMA systems is investigated by current literatures in slow fading channels, the channel estimation in the context of fast fading environments remains a challenge, which focuses on a desired tradeoff between the amount of pilot symbols and CSI estimation accuracy. For alleviating the above problem, in this paper, we develop a class of data-aided channel estimation schemes based on the log-likelihood ratio(LLR) calculation at the receiver to track the channel variations for OFDM-IDMA systems. Simulation results demonstrate that the proposed data-aided channel estimation scheme offers substantial performance gain over its conventional counterparts especially in the high-mobility case.

In this paper, we focus on pilot contamination problem in multi-cell massive multi-input multi-output (MIMO) systems. In general, orthogonal pilot across users and cells leads to bandwidth inefficiency. We propose an uplink transmission protocol design in which the pilot portions of users overlap with data from other cells and even partially overlap across cells. Semi-blind algorithms are applied to separate the data streams from user equipments (UEs). With the proposed protocol and semi-blind algorithms, the pilot contamination is greatly reduced. The simulation results show that with the help of semi-blind algorithm employing Constant Modulus Algorithm, the system performance is superior compared to that of the existing schemes.

Compared with single-carrier systems, multicarrier systems are more sensitive to synchronization offset. As one of multicarrier systems, offset quadrature amplitude modulation-based filter bank multicarrier (OQAM/FBMC) also suffers synchronization offset problem. Hence, accurate and reliable time offset (TO) and carrier frequency offset (CFO) synchronization schemes are necessary in OQAM/FBMC systems. This chapter firstly analyzes the effects of timing and frequency offsets in OQAM/FBMC, and several data-aided synchronization schemes with identical property are introduced in detail. A data-aided timing and CFO synchronization scheme is then presented by exploiting the conjugate-symmetry property of a properly designed training sequence. Finally, this chapter describes a case of Bayesian CFO estimation as an example of blind synchronization methods.

In this paper, a novel data-aided linear fitting-based (DALF-based) blind phase estimation method for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) is proposed. Similar to our previous work done in the pilot-based blind phase estimation method, the pilot subcarriers are used to transmit unknown amplitude modulation signals in order to improve spectral efficiency. But the so-called pilot subcarriers can be reduced to only two in the DALF-based method, while the conventional pilot-aided-based (PA-based) method requires almost four real pilot subcarriers. A performance comparison of the conventional PA-based and DALF-based phase estimation methods has been demonstrated through a 16-QAM CO-OFDM simulation. The results show that the performance of the proposed DALF-based method is better than the conventional one with higher SE and has the potential in the large capacity CO-OFDM systems.

This research study uses geophysical method (aeromagnetic) to identify hydrothermally altered structures which favour the inflow of hydrothermal fluid that usually brings about gold mineralisation in Egbe-Isanlu Schist Belt Area, North Central Nigeria. The application of data enhancement filtering algorithm such as reduction to the pole to the magnetic data aided in mapping of various hydrothermally altered structures that may favour gold mineralisation. The interpretation of the aero data set has enhanced a lot of hydrothermally altered structures that trend northeast-southwest(NE-SW). A number of hydrothermally altered structures are seen. Therefore the areas that are hydrothermally altered are potential sites for gold mineralisation, most importantly those areas that lie within or adjacent to major faults around Odogbe and Okolom in the North Central portion of the study area. Similarly, regions around Egbe in the western edge are suspected to be mineralized zones. The results obtained in this research study demonstrated that the geophysical tools adopted are powerful and effective means for gold mineral exploration. This method is unique because it is non-invasive which prevented any environmental degradation and it enhances the coverage of very large area. Keywords : Aeromagnetic Data; Isanlu; Structures; Gold Mineralisation; Hydrothermally Altered.

This paper is concerned with a uplink scheme for multicell large antenna systems. We study a channel estimation technique where partially decoded data is used to estimate the channel. We show that there are two types of interference components in this scheme that do not vanish even when the number of antennas grows to infinity. The first type, referred to as cross-contamination, is due to the correlation among the data signals from different users. The second type, referred to as self-contamination, is due to the dependency between the channel estimate and the estimation error. Cross contamination is in principle similar to pilot contamination in a conventional pilot-based channel estimation scheme, while self-contamination is unique for the data-aided scheme. For efficient use of the channel, the data part in a signaling frame is typically much longer than the pilot part for a practical system. Consequently, compared with pilot signals, data signals naturally have lower cross correlation. This fact reduces the cross-contamination effect in the data-aided scheme. Furthermore, self-contamination can be effectively suppressed by iterative processing. These results are confirmed by both analyses and simulations.

Over the past few years the assessment of the earthquake potential of large continental faults has increasingly relied on field investigations. State-of-the-art seismic hazard models are progressively complementing the information derived from earthquake catalogs with geological observations of active faulting. Using these observations, however, requires full understanding of the relationships between seismogenic slip at depth and surface deformation, such that the evidence indicating the presence of a large, potentially seismogenic fault can be singled out effectively and unambiguously. We used observations and models of the 6 April 2009, Mw 6.3, L'Aquila, normal faulting earthquake to explore the relationships between the activity of a large fault at seismogenic depth and its surface evidence. This very well-documented earthquake is representative of mid-size yet damaging earthquakes that are frequent around the Mediterranean basin, and was chosen as a paradigm of the nature of the associated geological evidence, along with observational difficulties and ambiguities. Thanks to the available high-resolution geologic, geodetic and seismological data aided by analog modeling, we reconstructed the full geometry of the seismogenic source in relation to surface and sub-surface faults. We maintain that the earthquake was caused by seismogenic slip in the range 3–10 km depth, and that the slip distribution was strongly controlled by inherited discontinuities. We also contend that faulting was expressed at the surface by pseudo-primary breaks resulting from coseismic crustal bending and by sympathetic slip on secondary faults. Based on our results we propose a scheme of normal fault hierarchization through which all surface occurrences related to faulting at various depths can be interpreted in the framework of a single, mechanically coherent model. We stress that appreciating such complexity is crucial to avoiding severe over- or under-estimation of the local seismogenic potential.

We propose a novel approach for data-aided estimation of the mixer gain and phase imbalances in the analog front-end of direct-conversion receivers. We estimate the inphase and quadrature imbalance (IQI) parameters isolated from the fading channel estimate and use the estimated IQI parameters for time-domain compensation. The motivation behind this approach is the scenario where the training symbols used for IQI estimation are transmitted from different antenna ports than those used for data transmission. In this scenario, the conventional composite IQI and channel estimate cannot be used for signal detection because the training and data symbols experience different channels. An example of this scenario is the long-term evolution (LTE) standard where the synchronization and broadcast signals are transmitted from different antenna ports than those used for data transmission. Numerical results show that our approach achieves up to 10 dB improvement using only two training symbols.

SUMMARYIn 2011, from August to November, the Monroe County Department of Public Health (MCDPH) investigated 47 salmonellosis cases. Geographical information software (GIS) was used to map the address locations of these cases. The resulting GIS analysis and culture information indicated that there were two distinct clusters of Salmonella that were geographically different. Pulsed-field gel electrophoresis (PFGE) testing was run at the New York State Department of Health Wadsworth Laboratory and identified S. Enteritidis (23 cases) and S. Typhimurium (10 cases). The epidemiological investigation identified Turkish pine nuts as the link between ill S. Enteritidis cases. Pine nut samples sent for laboratory testing were a PFGE match to human isolates with S. Enteritidis. A national recall of Turkish pine nuts ensued. A multistate outbreak was identified as a result of the initial investigation of MCDPH, in which 43 people were infected with the outbreak strain from five states. GIS software and shopper card data provided important tools in the epidemiological investigation.

[The Use of Indonesian Language (Word) in the Official Letter / Outgoing Mail of Kesiman Kertalagu Village, East Denpasar Sub District, Denpasar] This research entitled "The Use of Indonesian Language (Word) in the Official Letter / Outgoing Mail of Kesiman Kertalangu Village, East Denpasar Sub District, Denpasar". The use of Indonesian, especially the use of the word in the official / official letter out of Kesiman Kertalangu Village, Denpasar Timur Sub-district, Denpasar, still found some errors. In this study, which is the object of study, namely regarding the misuse of the word. Observation methods and note-taking techniques are used in data collection, descriptive synchronic qualitative methods are used to analyze data aided by inductive or deductive techniques, while informal methods are used to present results. In this study found several types of word usage errors. The types of word usage errors include: 1) preposition writing, 2) hypercorrect word writing, and 3) improper use of words.

Aiming at the problem of poor accuracy and small range of frequency estimation in the area of satellite-based AIS signals, this paper presents a novel data-aided estimation method based on the autocorrelation and DFT. The algorithm determines the principal value and the expansion of the frequency and then acquires high-precision estimation by data fitting. Based on that, other parameters can be estimated. Computer simulations were used to illustrate better estimation accuracy and a large estimation range.

Water is essential in providing nutrients, but contaminated water contributes to poor population health. Water quality and availability can change in unstructured situations, such as war. To develop a practical strategy to address poor water quality resulting from intermittent wars in Iraq, I reviewed information from academic sources regarding waterborne diseases, conflict and war, water quality treatment, and malnutrition. The prevalence of disease was high in impoverished, malnourished populations exposed to contaminated water sources. The data aided in developing a strategy to improve water quality in Iraq, which encompasses remineralized water from desalination plants, health care reform, monitoring and evaluation systems, and educational public health interventions.

We propose a full transmission link chromatic dispersion (CD) estimation technique for polarization-multiplexed coherent optical single carrier system using data-aided channel estimation and least square quadratic fit. New training sequences based on Chu sequence and Golay complementary pair are designed and compared for estimation performance against the ideal full-level Chu sequence for both QPSK and 16-QAM systems. The proposed technique is demonstrated in a 40-Gb/s coherent polarization multiplexed optical system over 2080-km fiber transmission for QPSK format and 80-Gb/s system over 1800-km fiber for 16-QAM format to verify its accurate and robust estimation performance.

Rapid and accurate synchronization constitutes a major challenge in deploying Ultra-Wideband impulse radio (UWB-IR) for indoor wireless communications. This paper develops a data-aided (DA) synchronization algorithm dispensing with searching procedures for UWB-IR communications. By adopting a stream of alternating orthogonal pulses, frame-level synchronization can be achieved without channel information. Without utilizing any searching procedure, the timing offset estimator is obtained in a closed form. Because exhaustive search can be avoided, both computational complexity and synchronization time are reduced. Simulations and comparisons are provided to illustrate the advantages of our design over the alternatives.

This study was undertaken to produce empirical evidence of validity and reliability of the item using a survey questionnaire Multiple Intelligences (MI) analyzed using Rasch Model for polythomus data aided by Winstep software.The questionnaire was conducted on 179 students from Selangor with MI instruments @ e-MyMICA.The results showed that all the PTMEA Corr is in positive values, where an item is able to distinguish between the ability of respondents. Based on the MNSQ infit and outfit range is 0.60-1.4 Statistical data obtained show that out 81 items 12 items from the instrument suggested to be omitted.

One of the biggest challenges in ultra-wideband (UWB) radio is the accurate timing acquisition for the receiver. In this article, we develop a novel data-aided synchronization algorithm for pulses amplitude modulation (PAM) UWB systems. Pilot and information symbols are transmitted simultaneously by an orthogonal code division multiplexing (OCDM) scheme. In the receiver, an algorithm based on the minimum average error probability (MAEP) of coherent detector is applied to estimate the timing offset. The multipath interference (MI) problem for timing offset estimation is considered. The mean-square-error (MSE) and the bit-error-rate(BER) performances of our proposed scheme are simulated. The results show that our algorithm outperforms the algorithm based on the maximum correlator output (MCO) in multipath channels.

This letter investigates Bayesian bounds on the mean-square error (MSE) applied to a data-aided carrier estimation problem. The presented bounds are derived from a covariance inequality principle: the so-called Weiss and Weinstein family. These bounds are of utmost interest to find the fundamental MSE limits of an estimator, even for critical scenarios (low signal-to-noise ratio and/or low number of observations). In a data-aided carrier estimation problem, a closed-form expression of the Weiss-Weinstein bound (WWB) that is known to be the tightest bound of the Weiss and Weinstein family is given. A comparison with the maximum likelihood estimator and the other bounds of the Weiss and Weinstein family is given. The WWB is shown to be an efficient tool to approximate this estimator's MSE and to predict the well-known threshold effect

The overall system efficiency of impulse radio communications relies critically on judicious allocation of transmission resources, a portion of which should be used to ensure successful timing acquisition. In data-aided mode, optimum timing offset estimation depends not only on the mechanism used for energy capture and the acquisition algorithm employed to recover timing information, but also on the training sequence (TS) pattern from which the timing information is to be extracted. Furthermore, the transmission resources used for timing have to be balanced with that for conveying information messages in order to strike desirable tradeoffs between timing accuracy and information rate. In Part I of this paper, data-aided timing offset estimation is derived based on the maximum likelihood (ML) criterion, where only symbol-rate samples are needed for low-complexity receiver processing. To minimize the mean-square timing errors of these ML synchronizers while at the same time maximizing the average system capacity, TS design and transmit power allocation are investigated in this paper. The optimum training pattern and the number, placement, and power distribution between training and information-bearing symbols are formulated as a resource allocation optimization problem whose solution optimizes system-level performance with the minimum amount of resources consumed.

This paper presents a new technique for detection of bursts in a wideband networking waveform of a software defined radio. For burst mode of transmission, the timing synchronization includes the recovery of time varying sampling clock offset and the detection of start of burst. Both these operations are very important in wideband networking radio operation as they directly affect the Medium Access adaptive time slot algorithm. The proposed burst detection scheme computes the decision metric on the basis of a specially designed training sequence. The threshold value for the proposed burst detection metric is very less dependent on channel conditions. It is shown that both the proposed algorithms achieve better performance as compared to existing algorithms. Computationally efficient prototype hardware implementation on Field Programmable Gate Array (FPGA) is also presented. Real-time hardware results have been presented to demonstrate the effectiveness of the proposed algorithms and architecture for systems requiring high data throughput.

The past few decades of ongoing war in Iraq has had a dramatic impact on the health of Iraq’s population. Wars are known to have negative effects on the social and physical environments of individuals, as well as limit their access to the available health care services. This paper explores the personal experiences of my family members, who were exposed to war, as well as includes information that has been reviewed form many academic sources. The data aided in providing recommendations and developing strategies, on both local and international levels, to improve the health status of the populations exposed to war.

An iterative low-complexity channel estimation algorithm for OFDM signals in frequency domain is presented. Algorithm uses initial channel estimation based on pilot subcarriers, 1-D adaptive Wiener filtering in the time direction and Maximum a-posteriori probability (MAP) estimation that uses both pilot and weighted data subcarriers. The final step is the simplified version of an iterative Expectation-Maximization (EM) algorithm that uses only single iteration to reduce total computational complexity.

Texture based classification of multidate ERS‐1 SAR image was carried out. It was found that multidate data aided in enhancement of classification accuracy. The overall classification accuracy was 64%. When speckles were reduced, the accuracy obtained was 53.2%. Principal component image of multidate SAR image gave an accuracy comparable to that of speckle filtered image. Discrimination ability was also examined and it was found that though despeckled image gave slightly better separability measure, the classification accuracy came down by about 10% as compared to that for original image when the texture based classification technique was used, which can be explained because an unfiltered image contains more information about texture.

Data detection burst mode systems requires that an accurate frequency of oscillator instabilities and doppler frequency be formed using the preamble. Current techniques manipulate the preamble‘s autocorrelation smaples to form the frequency estimate. In this paper we present a new estimator which uses the average of the product of adjacent autocorrelation samples. The algorithm has a feedforward structure which is easy to implement and a wide frequency acquisition range. The frequency estimate is unbiased and asymptotically reaches the Cramer Rao bound (CRB). From the derivation of the variance we calculate optimum weights using constrained optimisation. Implementation issues suggest it is possible to use a sub-optimal number of autocorrelation samples. Simulation results show that the corresponding sub-optimum weights have little effect on performance. Finally, the estimator‘s performance is compared to alternative techniques in the literature.