External Interference Sources Research Articles

An Improvement Method for Improving the Surface Defect Detection of Industrial Products Based on Contour Matching Algorithms.

Aiming at the problems of the poor robustness and universality of traditional contour matching algorithms in engineering applications, a method for improving the surface defect detection of industrial products based on contour matching algorithms is detailed in this paper. Based on the image pyramid optimization method, a three-level matching method is designed, which can quickly obtain the candidate pose of the target contour at the top of the image pyramid, combining the integral graph and the integration graph acceleration strategy based on weak classification. It can quickly obtain the rough positioning and rough angle of the target contour, which greatly improves the performance of the algorithm. In addition, to solve the problem that a large number of duplicate candidate points will be generated when the target candidate points are expanded, a method to obtain the optimal candidate points in the neighborhood of the target candidate points is designed, which can guarantee the matching accuracy and greatly reduce the calculation amount. In order to verify the effectiveness of the algorithm, functional test experiments were designed for template building function and contour matching function, including uniform illumination condition, nonlinear condition and contour matching detection under different conditions. The results show that: (1) Under uniform illumination conditions, the detection accuracy can be maintained at about 93%. (2) Under nonlinear illumination conditions, the detection accuracy can be maintained at about 91.84%. (3) When there is an external interference source, there will be a false detection or no detection, and the overall defect detection rate remains above 94%. It is verified that the proposed method can meet the application requirements of common defect detection, and has good robustness and meets the expected functional requirements of the algorithm, providing a strong technical guarantee and data support for the design of embedded image sensors in the later stage.

MAGPRIME: An Open‐Source Library for Benchmarking and Developing Interference Removal Algorithms for Spaceborne Magnetometers

AbstractMagnetometers are essential instruments in space physics, but their measurements are often contaminated by various external interference sources. In this work, we present a comprehensive review of existing magnetometer interference removal methods and introduce MAGPRIME (MAGnetic signal PRocessing, Interference Mitigation, and Enhancement), an open‐source Python library featuring a collection of state‐of‐the‐art interference removal algorithms. MAGPRIME streamlines the process of interference removal in magnetic field data by providing researchers with an integrated, easy‐to‐use platform. We detail the design, structure, and functionality of the library, as well as its potential to facilitate future research by enabling rapid testing and customization of interference removal methods. Using the MAGPRIME Library, we present two Monte Carlo benchmark results to compare the efficacy of interference removal algorithms in different magnetometer configurations. In Benchmark A, the Underdetermined Blind Source Separation (UBSS) and traditional gradiometry algorithms surpass the uncleaned boom‐mounted magnetometers, achieving improved correlation and reducing median error in each simulation. Benchmark B tests the efficacy of the suite of MAGPRIME algorithms in a boomless magnetometer configuration. In this configuration, the UBSS algorithm proves to significantly reduce median error, along with improvements in median correlation and signal to noise ratio. This study highlights MAGPRIME's potential in enhancing magnetic field measurement accuracy in various spacecraft designs, from traditional gradiometry setups to compact, cost‐effective alternatives like bus‐mounted CubeSat magnetometers, thus establishing it as a valuable tool for researchers and engineers in space exploration and magnetism studies.

OTA testing of near‐field and far‐field communication links

AbstractIn this work, near‐field and far‐field link measurement in metal enclosure environment is performed. The performance of near‐field and far‐field links are assessed using key performance indicators such as error vector magnitude, bit error rate, and signal‐to‐noise ratio. The metal enclosure is placed in an anechoic chamber, ensuring a stationary measurement environment. There are no external interference sources and the results are a function of near‐field and far‐field scenarios and hardware impairments. In measurements, software‐defined radios used for the transmission and reception of image data using the long‐term evolution‐advanced physical layer. Based on the results of the study, an optimum gain region can be determined where better key performance indicators are achieved. Furthermore, the frequency selectivity of the channel is reduced within the determined optimum gain region, leading to an improvement in the system's performance.

An Artificial Intelligence Radio Propagation Model Based on Geographical Information

In this article, a new wireless network planning propagation model is proposed, the datasets are continuous wave data from different cities, and the model is constructed based on the artificial neural network in machine learning and uses geographical information to do feature engineering. Six geographical information features are used as the input feature vectors of the model. The terrain type near the receiving point is a corrective factor affecting the propagation field intensity. To make the physical implications more explicit, two multilayer perceptron networks were designed, and the one-hot encoding of terrain types of five grids near the receiving point on the line between the receiving and transmitting points is taken as one of the input features of the second network. Through the model training and validation, and tested in actual scene, the model on the datasets of different cities has achieved good results. Compared with the traditional propagation model, such as the standard propagation model (SPM), this artificial intelligence model is more suitable for correction of data containing random disturbance and has a better simulation accuracy; the random disturbance includes external random interference sources, global positioning system offsets, and inaccurate maps.

Experimentally Validated Extended Kalman Filter Approach for Geomagnetically Induced Current Measurement

Geomagnetically induced currents (GICs) are referred to as the quasi-dc current flows in power networks, driven by complex space weather-related phenomena. Such currents are a potential threat to the power delivery capability of electrical grids. To mitigate the detrimental impacts of GICs on critical infrastructures, the GICs should be monitored in power systems. Being inherently dc from the power frequency point of view, the components of GICs are, however, challenging and costly to monitor in ac power grids. This article puts forward a novel methodology for the real-time estimation of GICs in power transformers. Such aim is attained by means of an extended Kalman filter (EKF)-based approach, mounted on the nonlinear state-space model of the transformer, whose parameters can be derived from standard tests. The proposed EKF-based algorithm employs the available measurements for the transformer differential protection. The proposed approach, relying on the differential current, can properly deal with the external sources of interference like harmonic excitation and loading. The EKF-based estimator presented is validated by simulation and experimental data. The results verify the ability of the proposed approach to robustly estimate the GIC level during various operating conditions.

Comparison of Metaheuristic Algorithms for Interface-Constrained Channel Assignment in a Hybrid Dynamic Spectrum Access – Wi-Fi Infrastructure WMN

In this work, we evaluate the application of four different metaheuristic optimisation algorithms for solving the channel assignment problem in a multi-radio multi-channel Wireless Mesh Network (WMN) using Dynamic Spectrum Access (DSA). The work advances a near optimal channel assignment (CA) in a WMN that uses DSA by applying soft computing methods. While CA in a WMN is well-studied, and CA for secondary user cognitive radio networks has also been studied in the literature, CA for our specific scenario of an infrastructure DSA-WMN is novel. This scenario poses new challenges because nodes are spread out geographically and so may have different allowed channels and experience different levels of external interference in different channels. A solution must meet two conflicting requirements simultaneously: 1) to avoid interference within the network and with external interference sources, and 2) maintain connectivity within the network; all while staying within the radio interface constraint, i.e., only assigning as many channels to a node as it has radios. We present a novel algorithm, used alongside the metaheuristic optimisation algorithms, which ensures the feasibility of solutions in the search space. Average Signal to Interference and Noise Ratio (<inline-formula> <tex-math notation="LaTeX">$SINR$ </tex-math></inline-formula>) over the network is used as the performance measure, with the goal of optimisation being to find the highest average <inline-formula> <tex-math notation="LaTeX">$SINR$ </tex-math></inline-formula>. This is a more realistic performance measure than the binary on/off conflict-based measures most common in the literature. Our energy-based method also has the unique advantage that it is protocol-agnostic, being able to avoid interference from external sources that use different protocols and standards. The algorithms that are compared in this work are Simulated Annealing (SA), the Genetic Algorithm (GA), Particle Swarm Optimisation (PSO), and Differential Evolution (DE). These algorithms were evaluated through the use of simulation in Network Simulator 3. Various parameters were experimented with for each of the employed algorithms. The resultant best set of parameters was used for the comparison of the four metaheuristic algorithms. It was found that the population-based algorithms (PSO, GA, and DE) all perform satisfactorily for this problem, although DE is superior to the others. SA can give acceptable solutions, but performs poorly in comparison to the population-based algorithms. The paper also considers the computational complexity of the methods. It is found that SA and DE perform well in this regard.

Detecting GNSS Jamming and Spoofing on Android Devices

<h3>Abstract</h3> Global navigation satellite system (GNSS) location engines on Android devices provide location and navigation utility to billions of people worldwide. However, these location engines currently have very limited protection from threats to their position, navigation, and time (PNT) solutions. External sources of radio frequency interference (RFI) can render PNT information unusable. Even worse, false signals or spoofing can provide a false PNT solution to Android devices. To mitigate this, four detection methods were developed and evaluated using native location parameters within Android: Comparing the GNSS and network locations, checking the Android mock location flag, comparing the GNSS and Android system times, and observing the automatic gain control (AGC) and carrier-to-noise density (C/N₀) signal metrics. These methods provide a powerful means to significantly increase the robustness of the Android GNSS-based PNT solution and are implemented in the GNSSAlarm Android application to demonstrate real-time jamming and spoofing detection.

External Dynamic InTerference Estimation and Removal (EDITER) for low field MRI.

Point-of-care MRI requires operation outside of Faraday shielded rooms normally used to block image-degrading electromagnetic interference (EMI). To address this, we introduce the EDITER method (External Dynamic InTerference Estimation and Removal), an external sensor-based method to retrospectively remove image artifacts from time-varying external interference sources. The method acquires data from multiple EMI detectors (tuned receive coils as well as untuned electrodes placed on the body) simultaneously with the primary MR coil during and between image data acquisition. We calculate impulse response functions dynamically that map the data from the detectors to the time varying artifacts then remove the transformed detected EMI from the MR data. Performance of the EDITER algorithm was assessed in phantom and in vivo imaging experiments in an 80mT portable brain MRI in a controlled EMI environment and with an open 47.5mT MRI scanner in an uncontrolled EMI setting. In the controlled setting, the effectiveness of the EDITER technique was demonstrated for specific types of introduced EMI sources with up to a 97% reduction of structured EMI and up to 76% reduction of broadband EMI in phantom experiments. In the uncontrolled EMI experiments, we demonstrate EMI reductions of up to 99% using an electrode and pick-up coil in vivo. We demonstrate up to a nine-fold improvement in image SNR with the method. The EDITER technique is a flexible and robust method to improve image quality in portable MRI systems with minimal passive shielding and could reduce the reliance of MRI on shielded rooms and allow for truly portable MRI.

Testing RFoF link for transmitting HF-OTHR signal between transmitter and receiver shelters

HF-OTHR site contains two equipment shelters, up to 1 km away from each other, that need to be connected for transmitting a FMCW signal. This connection, if realized using a coaxial cable, has shown itself to be vulnerable to external electromagnetic discharges, which can damage the sensitive radar equipment. This paper explores and tests the possibility of using Radio-Frequency-over-Fiber (RFoF) link as an alternative to a coaxial cable for transmission of signal, in order to ensure the immunity from external sources of electromagnetic interference (EMI).

Combined adaptive antenna array and adaptive channel equalizer, based on multichannel fast recursive least squares algorithms

An adaptive antenna array (AAA) is a sort of directional antennas, which is able to suppress the signals of the interference sources. The AAA works well if there is no multipath propagation of the information signal. A device, which removes the multipath effects, is an adaptive equalizer. However, the independent AAA and equalizer do not work well if the interferences and multipath exist simultaneously. The purpose of this paper is to present a new efficient solution of the task by using of the AAA, whose weights are shared with the weights of the fractionally-spaced feed-forward (FF) part of the equalizer. The array output signal is combined with that of the feed-backward (FB) part of the equalizer. The array and such distributed equalizer operate as an indivisible adaptive filter, providing good performance and ability to receive the multipath information signals in the presence of the signals of the external interference sources. Because the FF part of the equalizer operates at the up-sampled rate, which is a few times higher than the information symbols rate, but the FB filter operates at the symbol rate, the computationally efficient fast recursive least squares (RLS) algorithms cannot be used directly in the considered adaptive unit. To solve this problem, it is proposed to use polyphase representation of the FF part of the equalizer. In this case, the architecture of the adaptive unit is viewed as a multichannel adaptive filter with unequal number of weights in channels. The paper presents the architecture of the adaptive unit and the details of its equalizer part. The mathematical description of a multichannel fast adaptive filtering algorithm, called stabilized fast a posteriori sequential technique (FAEST), fitted for the weights calculation of the considered unit is also presented. The verification of the proposed adaptive unit has been carried out via simulation, using a linear array with sixteen omnidirectional antennas, which operates in the conditions of –30 dB signal-to-interference ratio (SIR), 10…30 dB signal-to-noise ratio (SNR), receives the phase shift keying (8-PSK) desired signal, passed through a two-rays communication channel with about –65 dB gaps in the channel amplitude-frequency response. In the steady-state, the proposed adaptive unit demonstrates about –100 dB radiation pattern gaps towards the interference sources and the transient response with less than 500 symbols duration. The simulation demonstrates the ability of the proposed unit simultaneously to steer the main lobe of antenna array radiation pattern towards the desired signal source without a priori search of its angular location and to remove the signals of the external interferences and intersymbol interference in the array output signal. Due to these properties, the proposed AAA/equalizer can be used in equipment of modern mobile communication systems.

Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments.

In this paper, we propose a methodology to use the received signal strength indicator (RSSI) available by the protocol stack of an installed Wireless Sensor Network (WSN) at an electric-power-system environment (EPS) as a tool for obtaining the characteristic of its communication channel. Thereby, it is possible to optimize the settings and configuration of the network after its deployment, which is usually run empirically without any previous knowledge of the channel. A study case of a hydroelectric power plant is presented, where measurements recorded over a two-month period were analyzed and treated to obtain the large-scale characteristics of the radiofrequency channel at 2.4 GHz. In addition, we showed that instantaneous RSSI data can also be used to detect specific issues in the network, such as repetitive patterns in the transmitted power level of the nodes, and information about its environment, such as the presence of external sources of electromagnetic interference. As a result, we demonstrate the practical use of the RSSI long-term data generated by the WSN for its own performance optimization and the detection of particular events in an EPS or any similar industrial environment.

TECHNOLOGICAL APPROACH TO SOLVING THE PROBLEM OF MINIMIZING THE INFLUENCE OF DESTABILIZING FACTORS ON THE WORK OF DISTRIBUTED STRUCTURES OF THE GROUND-ROCKOTECHNICAL COMPLEX IN AN INTEGRAL PROJECT «OBJECT-SYSTEM»

Mobile structures of the ground-based robotic complex (RTC) are investigated as an active component formation of an integrated project “object-system”, which is operated in a destabilizing environment. The relevant problem of minimizing the influence of external destabilizing factors on the operation of mobile spatially-distributed structures of the ground-based RTC is stated in the descriptions of the conceptual apparatus of complex, poorly formalized multicomponent technical systems. Following the logic of this approach, the basic principles of distributed control are determined and their applications are implemented in the mobile structures of the ground-based RTC with elements of subsidiarity. The quintessence of the latter is represented by the technology of multi-antenna MIMO systems, which made it possible to determine the trade-offs of using classical transmission methods and strategies for receiving and processing MIMO signals in the multi-sensory channels of the information-control system (ICS) and radio communication with the data transmission system and commands. Given the complexity of performing the stated tasks, a set of technological functions of reducing the influence of destabilizing factors and their practical variations in the algorithms for obtaining the target result are proposed. A situational model of reducing (minimizing) information losses at the output of the information-control system of the ground-based robotic complex under destabilization has been built. Options have been proposed to achieve the target result: integration of structural and parametric adaptation methods, MIMO technologies, code division multiplexing techniques with CDMA channels, taking into account the heterogeneity factor of information exchange channels and the artificial redundancy of the system itself with respect to the number of external interference sources.

Accuracy improvement of quantitative analysis in VIS-NIR spectroscopy using the GKF-WTEF algorithm.

The extraction of effective information in visible-near-infrared (VIS-NIR) spectroscopy is crucial and difficult for spectral analysis. In this research, an algorithm of wavelet feature extraction based on the Gaussian kernel function (GKF-WTEF) was developed to suppress the influence of external interference on VIS-NIR spectroscopy and improve the accuracy of quantitative analysis. This algorithm takes the root-mean-square error of the prediction set (RMSEP) of the model, which is established by partial least-squares regression, as the optimization criteria. First, the optimal type of wavelet function, the decomposition level, and the Gauss kernel function central frequency band are determined according to the RMSEP. Second, the Gauss kernel function bandwidth is determined by Newton's method. Then, the Hadamard product of the Gaussian kernel function and the wavelet coefficient is obtained. Finally, the wavelet coefficients after the Hadamard product can be reconstructed to obtain the spectral data after feature extraction. In order to verify the effectiveness of this algorithm, the difference in the optical parameters of the polyvinyl chloride material container was used as an external interference source. And the spectrum of Intra-lipid and India-ink mixed solution with different concentrations was collected therein. The volume fraction of India-ink in complex mixed solution was quantitatively analyzed by using the RMSEP and the average relative error of the prediction set as the evaluation criteria. The research results demonstrated that the Gaussian-wavelet transform feature extraction algorithm is an effective pretreatment method, it can satisfactorily suppress the influence of external interference on the spectrum, and it can improve the analytical accuracy of VIS-NIR spectroscopy.

A Slotted Sense Multiple Access Protocol for Timely and Reliable Data Transmission in Dynamic Wireless Sensor Networks

A wireless medium access control protocol that uses a topology-dependent slot schedule is vulnerable to link failures. This becomes severer in industrial fields due to node mobility and various obstructions unfriendly to wireless communication. The proposed protocol allocates a big sharable slot (SS) to each tree level, producing a topology-independent schedule that makes the protocol highly responsive to the changes of topology. Then, the nodes at the same level use carrier sense multiple access (CSMA)/CA for data transmission and channel hopping to cope with the varying condition of a channel. The use of CSMA/CA and channel hoping makes data transmission reliable against internal and external interferences. Another feature is that every node gets its SS using a slot generation function independently of other nodes. Simulations and experiments verify that the proposed protocol achieves good performance in terms of packet delivery ratio and energy efficiency against the variation of multipath fading, various external sources of interference, and node mobility.

An SVM-Based Method for Classification of External Interference in Industrial Wireless Sensor and Actuator Networks

In recent years, the adoption of industrial wireless sensor and actuator networks (IWSANs) has greatly increased. However, the time-critical performance of IWSANs is considerably affected by external sources of interference. In particular, when an IEEE 802.11 network is coexisting in the same environment, a significant drop in communication reliability is observed. This, in turn, represents one of the main challenges for a wide-scale adoption of IWSAN. Interference classification through spectrum sensing is a possible step towards interference mitigation, but the long sampling window required by many of the approaches in the literature undermines their run-time applicability in time-slotted channel hopping (TSCH)-based IWSAN. Aiming at minimizing both the sensing time and the memory footprint of the collected samples, a centralized interference classifier based on support vector machines (SVMs) is introduced in this article. The proposed mechanism, tested with sample traces collected in industrial scenarios, enables the classification of interference from IEEE 802.11 networks and microwave ovens, while ensuring high classification accuracy with a sensing duration below 300 ms. In addition, the obtained results show that the fast classification together with a contained sampling frequency ensure the suitability of the method for TSCH-based IWSAN.

Enhanced Common-Mode Noise Rejection Method Based on Impedance Mismatching Compensation for Wireless Capsule Endoscopy Systems

Common-mode noise (CMN) is an unresolved problem in wireless capsule endoscopy (WCE) systems. In a WCE system, CMN originates from various electric currents found within the human body or external interference sources and causes critical demodulation performance degradation. The differential operation, a typical method for the removal of CMN rejection, can remove CMN by subtracting two signals simultaneously received by two reception sensors attached to a human body. However, when there is impedance mismatching between the two reception sensors, the differential operation method cannot completely remove CMN. Therefore, to overcome this problem, we propose an enhanced CMN rejection method. The proposed method performs not only subtraction but also addition between two received signals. Then a CMN ratio can be estimated by sufficient accumulation of division operation outcomes between the subtraction and addition outputs during the guard period. Finally, we can reject the residual CMN by combining the subtraction and addition outputs.

The external–internal loop of interference: Two types of attention and their influence on the learning abilities of mice

Attention is a component of the working memory system, and is responsible for protecting task-relevant information from interference. Cognitive performance (particularly outside of the laboratory) is often plagued by interference, and the source of this interference, either external or internal, might influence the expression of individual differences in attentional ability. By definition, external attention (also described as “selective attention”) protects working memory against sensorial distractors of all kinds, while internal attention (also called “inhibition”) protects working memory against emotional impulses, irrelevant information from memory, and automatically-generated responses. At present, it is unclear if these two types of attention are expressed independently in non-human animals, and how they might differentially impact performance on other cognitive processes, such as learning. By using a diverse battery of four attention tests (with varying levels of internal and external sources of interference), here we aimed both to explore this issue, and to obtain a robust and general (less task-specific) measure of attention in mice. Exploratory factor analyses revealed two factors (external and internal attention) that in total, accounted for 73% of the variance in attentional performance. Confirmatory factor analyses found an excellent fit with the data of the model of attention that assumed an external and internal distinction (with a resulting correlation of 0.43). In contrast, a model of attention that assumed one source of variance (i.e., “general attention”) exhibited a poor fit with the data. Regarding the relationship between attention and learning, higher resistance against external sources of interference promoted better new learning, but tended to impair performance when cognitive flexibility was required, such as during the reversal of a previously instantiated response. The present results suggest that there can be (at least) two types of attention that contribute to the common variance in attentional performance in mice, and that external and internal attentions might have opposing influences on the rate at which animals learn.

A Lightweight Classification Algorithm for External Sources of Interference in IEEE 802.15.4-Based Wireless Sensor Networks Operating at the 2.4 GHz

IEEE 802.15.4 is the technology behind wireless sensor networks (WSNs) and ZigBee. Most of the IEEE 802.15.4 radios operate in the crowded 2.4 GHz frequency band, which is used by many technologies. Since IEEE 802.15.4 is a low power technology, the avoidance of interference is vital to conserve energy and to extend the lifetime of devices. A lightweight classification algorithm is presented to detect the common external sources of interference in the 2.4 GHz frequency band, namely, IEEE 802.11-based wireless local area networks (WLANs), Bluetooth, and microwave ovens. This lightweight algorithm uses the energy detection (ED) feature (the feature behind received signal strength indication (RSSI)) of an IEEE 802.15.4-compliant radio. Therefore, it classifies the interferers without demodulation of their signals. As it relies on time patterns instead of spectral features, the algorithm has no need to change the channel. Thus, it allows the radio both to stay connected to the channel and to receive while scanning. Furthermore, it has a maximum runtime of merely one second. The algorithm is extensively tested in a radio frequency anechoic chamber and in real world scenarios. These results are presented here.

Joint Topology-Transparent Scheduling and QoS Routing in Ad Hoc Networks

This paper considers the problem of joint topologytransparent scheduling (TTS) and quality-of-service (QoS) routing in ad hoc networks and presents a joint scheme for the problem. Due to its ability to guarantee single-hop QoS support, TTS is chosen as the underlying medium-access-control (MAC) protocol. By being built on top of TTS, this paper first designs methods for bandwidth estimation and allocation (BWE and BWA, respectively) to provide QoS support without knowledge of slot status information, and then, estimates and allocates nonassigned eligible bandwidth for best effort (BE) flows. With these bandwidth management methods, this paper proposes a QoS routing protocol for a mixture of QoS and BE flows. Idealized simulation results based on the standard radio model, which ignores external sources of radio interference and protocol inefficiencies, reveal that the proposed joint scheme can provide a reduction of at least 93% in QoS violation rates and a reduction of 78%-89% in control overhead compared with the conventional dynamic source routing (DSR)/IEEE 802.11 technique. A comparison with another conventional technique, i.e., DSR/carrier sense multiple access (CSMA), also reveals that the proposed joint scheme can reduce QoS violation rates by at least 93%. In addition, the proposed joint scheme can provide an increase of 31%-104% in aggregate throughput over two representative QoS routing protocols while achieving a reduction of approximately 93% in QoS violation rates. The performance improvement to be achieved under a realistic radio model is yet to be determined.

Subjective cognitive complaint in healthy older adults: Identification of major domains and relation to objective performance

ABSTRACTThis study analyzed complaints across a range of memory domains in middle-aged and older adults, as well as assessed their relationship with objective cognitive performance and personal characteristics. A total of 115 community-dwelling, healthy adults between the ages of 45 and 87 completed the Self-Evaluation Questionnaire (QAM) and were tested with a comprehensive neuropsychological battery. A principal component analysis identified seven dimensions of complaint. Difficulty inhibiting internal and external sources of interference when learning or remembering something was the main area of complaint and it was correlated with word-list recall and Digit Symbol. We identified complaints related to a set of memory failures that appear to be more detrimental to autonomy and safety. These were correlated with a measure of functional autonomy and might, therefore, indicate more severe difficulties. Overall, this study provides indications regarding the main domains of memory complaints and identifies which complaints are most reflective of objective cognitive problems.