Types Of Processors Research Articles

Research on Multiplication Routine Based on Reconfigurable Four-Valued Logic Processor

Despite the indispensable role of traditional electronic computers in modern society, their limitations in parallel processing capabilities, bit-width constraints, and processor bit-width are becoming increasingly apparent, especially when handling large-scale datasets and complex computational tasks. Although hardware technology and algorithm optimization continue to advance, the arithmetic units of traditional computers—adders—remain constrained by carry delay and bit-width limitations. This bottleneck is particularly pronounced in multiplication operations, mainly when adders are used for partial product accumulation. However, since 2018, the emergence of a new type of Reconfigurable Four-Valued Logic Electronic Processor (RFLEP) has provided a potential solution to these traditional limitations. With its large processor bit-width, flexible bit grouping capabilities, and dynamic hardware function reconfiguration features, this processor has brought revolutionary changes to the field of computing. In this context, this paper proposes and implements a Reconfigurable Four-Valued Logic Multiplication Routine (RFLMR) tailored explicitly for the RFLEP. The RFLMR utilizes the Modified Signed-Digit (MSD) representation method in multi-valued logic combined with the M transformation in four-valued logic to generate partial products. These partial products are then efficiently summed in parallel using the JW-MSD parallel adder, achieving the rapid execution of multiplication operations. Experimental results demonstrate that the multiplication routine based on the RFLEP performs multiplication operations accurately and meets theoretical expectations regarding implementation efficiency and performance. This research not only provides new ideas for developing next-generation high-performance computing systems but also paves the way for exploring more efficient and powerful computing models, heralding a profound transformation in future computing technology.

249 Effects of sorghum silage kernel processing on growth performance and blood metabolites of beef heifers

Abstract Our previous studies suggested that using a shredlage (SHRD) processor or a conventional (CONV) sorghum kernel processor leads to similar apparent total tract nutrient digestibility of whole plant sorghum silage (WPSS). This study evaluated the effects of feeding WPSS harvested using different kernel processors (CONV vs. SHRD), on growth performance of beef heifers. Grain sorghum (ADV2450IG; Advanta Seeds, Argentina) was harvested at the hard-dough stage with a Class Jaguar 950 (Harsewinkel, Germany), switching the kernel processor to generate the forage material for the two treatments: CONV and SHRD. The material was bagged in two 2.7 m diameter bags and allowed to ferment for 3 mo. Black Angus heifers [n = 96; body weight (BW) = 15 ± 1 mo, 249.6 ± 28.6 kg] were blocked by initial BW, and randomly assigned to pens (8 heifers/pen, 6 pens/treatment). Diets consisted, all in DM basis, of WPSS of each respective type (SHRD or CONV) at 90.5%, expeller soybean meal at 7.0%, and a vitamin-mineral-NNP concentrate at 2.5%. The experiment consisted of a 14-d adaptation period, followed by a 56-d growing period; and feed was offered once daily. Data were analyzed as a randomized complete block design, using pen as the experimental unit, with the fixed effect of treatment and the random effect of block. No differences were observed (P > 0.10) for final BW, dry matter intake, and residual feed intake. However, CONV fed heifers tended to gain more BW per day (ADG, 0.83 vs. 0.77 kg/d; P = 0.07) and had greater gain to feed ratio (GF, 0.083 vs. 0.075 kg/kg; P = 0.05) and greater Kleiber ratio (KR, 12.1 vs 11.2 g/kg; P = 0.05) as compared with SHRD fed heifers. Furthermore, performance calculated dietary Net Energy of gain (NEg) in CONV fed heifers tended to be greater than that for SHRD (0.70 vs. 0.65 Mcal/kg of diet DM, respectively; P = 0.06). Moreover, blood serum from CONV fed heifers had 16% greater total bilirubin (P = 0.04), 12% greater cholesterol (P = 0.02), and slightly greater non esterified fatty acids (P = 0.03) concentrations. Noteworthy, serum concentrations of total bilirubin were correlated (P ≤ 0.03) with ADG, GF, KR and NEg. In conclusion, the type of kernel processor utilized for the harvest of sorghum silage may have an impact on feed efficiency of beef cattle. These differences could be related to changes on the site of utilization of nutrients, particularly starch; what could also explain the differences on blood metabolites. However, further research is needed to help explain these findings.

Visualization at exascale: Making it all work with VTK-m

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. We document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer.

Comparing Audiological Outcomes of Conventional and AI-Upgraded Cochlear Implant Speech Processors.

In current age of technology, artificial intelligence is used in the medical field to improve the quality and accuracy in patient care and achieve better clientele satisfaction. The use of artificial intelligence in the field of hearing rehabilitation and cochlear implantation has an immense scope and it enhances the accuracy in placement of electrode array, forecasting site of surgical location and optimization of speech processing. This study aims to compare the audiological outcomes of conventional versus artificial intelligence technology enabled cochlear implant speech processors. Additionally, it compares the individual performance and satisfaction level with use of both types of speech processors. All children who underwent upgradation of their cochlear implant speech processors at a tertiary care cochlear implant centre with artificial intelligence enabled speech processors were included in the study. The comparison of audiological outcomes of conventional versus artificial intelligence integrated speech processors were assessed by using Aided Audiometry, Categories of Auditory Perception Score and Speech Intelligibility Rating scale. Children using the basic model cochlear implant speech processor which was provided at the time of implantation are referred as conventional cochlear implant speech processor user. Their speech processors were subsequently upgraded with current generation artificial intelligence integrated speech processors which is referred here as artificial intelligence upgraded cochlear implant speech processor. During the study, a total of thirty-four (34) patients underwent upgradation of cochlear implant speech processors. The mean categories of auditory perception score were 11.58 and 11.94 using conventional and artificial intelligence upgraded speech processor respectively. The mean speech intelligibility rating score was 4.5 and 4.6 respectively. The audiological outcomes of conventional speech processors are comparable with those using artificial intelligence enabled speech processors. However, the clientele satisfaction in respect to quality of sound, ease of listening in difficult listening environment, smart connectivity options for both phone and television is available and better with the artificial intelligence enabled cochlear implant speech processor. This also has the advantages of auto switching of programming with change in ambient noise, better signal to noise ratio and better 360* hearing.

ARM-CO-UP: ARM CO operative U tilization of P rocessors

HMPSoCs combine different processors on a single chip. They enable powerful embedded devices, which increasingly perform ML inference tasks at the edge. State-of-the-art HMPSoCs can perform on-chip embedded inference using different processors, such as CPUs, GPUs, and NPUs. HMPSoCs can potentially overcome the limitation of low single-processor CNN inference performance and efficiency by cooperative use of multiple processors. However, standard inference frameworks for edge devices typically utilize only a single processor. We present the ARM-CO-UP framework built on the ARM-CL library. The ARM-CO-UP framework supports two modes of operation – Pipeline and Switch. It optimizes inference throughput using pipelined execution of network partitions for consecutive input frames in the Pipeline mode. It improves inference latency through layer-switched inference for a single input frame in the Switch mode. Furthermore, it supports layer-wise CPU/GPU DVFS in both modes for improving power efficiency and energy consumption. ARM-CO-UP is a comprehensive framework for multi-processor CNN inference that automates CNN partitioning and mapping, pipeline synchronization, processor type switching, layer-wise DVFS , and closed-source NPU integration.

Selection of speech processor in cochlear implant patients: experience in a tertiary hospital

Background There are two types of speech processors used in CI devices: behind-the-ear (BTE) and off-the-ear (OTE). Objectives This study aimed to investigate the characteristics of patients and revision cases in relation to the type of speech processors. Materials and methods A retrospective review of 452 ears that underwent CI was performed. Results Children with severe inner ear anomalies (91.7%) more frequently preferred BTE speech processors than those without severe inner ear anomalies (p = .000). The magnet strength used in OTE speech processor users was significantly higher than in BTE speech processor users (p = .002). In cochlear implantees who underwent surgery before 12 months of age, the magnet strength in the revision group was greater than in the non-revision group (p = .025). Conclusions and significance Overall, our findings suggest factors to consider when choosing the type of speech processor and modifying the magnet strength of the implant device. The choice between BTE and OTE speech processors led to different required magnet strengths, contributing to the occurrence of skin flap inflammation.

AET Volume 2 Nomor 3] Environmental, medical, and educational research sustainability in the age of technology: An editorial review

The six articles on Applied Engineering and Technology Volume 2 No 3 December 2023 presented have significant relevance in current engineering and technological developments to the three sectors: Environmental sustainability, Medicine, and Education. First, in an era that increasingly pays attention to environmental sustainability, as reflected in efforts to mitigate the environmental impact of the oil and gas industry, Effiom's research on developing bio-based drilling fluid becomes relevant and reflects the industry's efforts to adopt environmentally friendly solutions in the oil and gas exploration process [1]. This research develops and optimizes local pear seed-based biocyte fluid. Throughout the world, oil exploration and exploitation have had severe environmental impacts. So, it is very important to develop drilling fluid for oil exploration. This research optimizes drilling fluids by using biodegradable materials. The optimized drilling fluid contains environmentally friendly and cost-effective characteristics and is expected to be widely used in oil exploration, reducing adverse environmental impacts. Princewill et al. [2] conducted a safety and economic evaluation of boil-off gas (BOG) in global petroleum (LPG) storage tanks. BOG production impacts safety and economic profitability in the liquefied petroleum gas supply chain. This research evaluates BOG production due to heat leaks in storage tanks by analyzing thermodynamic properties and heat transfer equations. The research results show that maintaining isolation and external factors minimizes BOG formation. Therefore, this research provides essential guidance and suggestions for the safety and economic benefits of the liquefied petroleum gas supply chain. Finally, Yudanto et al. [3] used computational fluid dynamics (CFD) and Taguchi methods to calculate the CPU cooling system. The performance and stability of electronic devices are significant for users in today's rapid development of information technology. This study analyzes the impact of different cooling system configurations on CPU temperatures and provides practical insights into electronic thermite design. Through numerical simulations, the research results provide an essential reference for developing computer hardware design. Second, Agughasi and Srinivasiah [4] developed a semisupervised method for characterizing multiple chest X-ray images in the medical field. Accurate marker images are critical for training supervised learning models in medical image handling. However, manually tagging a large number of images requires time and effort. Therefore, this study suggests using unsupervised cluster technology-based K-Means and Self-Organizing Maps to produce reliable images. In this way, medical imaging processing costs can be reduced significantly, speeding up the research and application process. Meanwhile, in the education sector, Mariscal et al. [5] developed the mobile application MobILcaps to improve information literacy for social science students in higher education as a relevant instrument to facilitate teaching. Information literacy is crucial for developing individuals and society in today's information era. Based on cognitive, constructivist, and connectivity theories, this application has provided multimedia resources for students to facilitate independent learning. By working with teachers and students, this application provides practical tools and avenues for increasing students' information literacy levels. In addition, Riva et al. [6] developed AdPisika as an electronic learning system tailored to improve student academic achievement. In today's educational environment, personalized learning is critical to increasing the impact of learning for students. This research, based on learning style models and machine learning algorithms, personally optimizes learning materials, thereby improving students' learning performance. This system has significantly improved students' academic performance through experimental verification, providing practical ways to align education. In conclusion, these studies make essential contributions and provide valuable references and guidance for applying engineering and technology research and practice in the fields of Environmental sustainability, Medicine, and Education. Future research could investigate the depth and breadth of these areas and test the feasibility and effectiveness of such research through practical applications and experimental testing. In the context of environmental sustainability potential research includes exploration in the development of bio-based drilling fluid using alternative materials that are more environmentally friendly, research on green technology to reduce the impact of boil-off gas (BOG) in the LPG industry, and research on processor types and system configurations as well as the development of more efficient materials and more innovative cooling technology to improve the performance of the CPU cooling system. In the medical field, deepen semi-supervised labeling methods for medical image processing can focus on developing more sophisticated algorithms and further validation of various medical datasets. Meanwhile, in the educational context, developing broader mobile applications could increase information literacy. It could be useful if it adapted to various disciplines and research on integrating more advanced AI technology for adaptive e-learning systems more effectively.

Scheduling energy consumption-constrained workflows in heterogeneous multi-processor embedded systems

Heterogeneous multi-processor architecture which achieves rich functionalities with different types of processors, is widely used to provide powerful calculating capability while keeping energy consumption under control. Although this architecture can improve system flexibility for adapting to future requirement variations, it results in a complex multi-task scheduling problem for system designers to produce a reasonable schedule that satisfies all deadline, data dependency, and energy limitation constraints. In this paper, we concentrate on the energy consumption-constrained scheduling problem of workflows in heterogeneous multi-processor embedded systems. First, we model the workflows and energy consumption of processors, and formulate the energy consumption-constrained scheduling problem as an optimization one whose objective is to shorten the schedule length of workflows as much as possible. Then, with an improved energy per-assignment strategy, we propose a novel energy difference coefficient-based scheduling algorithm to produce an approximately optimal allocation of processors, frequencies, and start times for each task while guaranteeing that the data dependency and energy limitation constraints are satisfied. Finally, experiments on both randomly-generated and real-world workflows are conducted to verify the reliability and efficiency of the proposed approach.

Performance evaluation of LU matrix decomposition using the SYCL standard

The object of this study is the performance of the SYCL standard tools when solving the LU matrix decomposition problem. SYCL is a fairly new technology for parallel computing in heterogeneous systems, so the topic of evaluating the performance of the standard on specific tasks in the field of parallel computing is relevant. In the study, the algorithm of parallelized LU decomposition of a square matrix was implemented by means of the SYCL standard and standard C++, and an experiment was conducted to test the implementation in a heterogeneous system with several types of processors. During testing, the program received square matrices of various dimensions as input, and the output was the execution time of the LU schedule on the selected processor. The obtained results, presented in the form of tabular and graphic data, show the advantage of the implementation of the SYCL standard over ordinary C++ by more than 2 times when using a graphics processor. It was experimentally shown that the implementation on SYCL is almost not inferior in speed to the implementation on ordinary C++ when executed on a central processor. Such results are caused both by the high possibility of parallelizing the LU schedule algorithm itself, and by the great work of the developers of the standard on its optimization. The obtained results indicate the possibility of speeding up the solution of the LU decomposition of the matrix and similar algorithms by means of SYCL when using heterogeneous systems with processors optimized for data parallelism. The results of the study can be used in justifying the choice of technology for solving LU matrix decomposition problems or problems with a similar parallelization scheme.

Method of assessment of energy intensity of public communication radio equipment with software adjustable working frequency for determination of interruption protection indicators

The ability of modern departmental communication systems to perform tasks in conditions of radio-electronic suppression by the enemy characterizes their immunity to interference. It is known that the interference protection of radio equipment in conditions of enemy radio reconnaissance and electronic suppression can be described by a set of probability indicators that characterize its secrecy (energy) and interference resistance. Secrecy (energy) is the ability of departmental communication systems to counteract the enemy's radio reconnaissance means, which are aimed at detecting the fact of the departmental communication system's operation, determining the parameters of its radio emissions, intercepting information for further deliberate radio-electronic and electromagnetic interference. One of the methods that significantly increases the secrecy of departmental communication systems is the use of signals with software-defined frequency conversion. These signals are a set of radio pulses (signal elements) whose frequencies change over time according to the law of pseudorandom sequence. The enemy searches for and detects the elements of these signals in a wide frequency band. This search is carried out under conditions of partial a priori uncertainty regarding their spectral-time structure using panoramic receivers. It should be noted that the basis of the radio reconnaissance means of the world's leading states is Fourier processors, which perform Fourier transforms from the implementation of a set of input signals. When designing and developing methods for interference protection, the problem of evaluating their energy stealth arises. Known research results and existing methodologies allow for a simplified assessment of the energy stealth of radio equipment with software frequency hopping under time constraints for decision making and do not take into account the peculiarities of the construction of modern panoramic analysis tools. In particular, the known methodologies do not take into account the peculiarities of the process of frequency-time searching for elements of such signals in a wide frequency range using panoramic receiving devices based on the complex application of different types of Fourier processors, the order of spectral-time processing of signal elements at the output of Fourier processors, requirements for their threshold sensitivity and dynamic signal range. Therefore, the article proposes a methodology for evaluating the stealthiness of communication systems with software-defined frequency tuning to determine the indicators of interference protection based on Fourier processors in the conditions of the opponent's use of modern radio-electronic intelligence tools.

A quantum algorithm for solving weapon target assignment problem

Quantum computers, known to have the potential for exponential speedup in solving some problems due to their superposition property, are expected to facilitate the solution of NP-hard optimisation problems. This study proposes a quantum algorithm to solve the weapon target assignment problem (WTAP), one of the NP-hard optimisation problems. The proposed quantum algorithm is a gate-based approach, and scenario examples are executed on Qiskit quantum computing platform and IBM Lima quantum computer with Falcon r4T processor type. The results manifest that the proposed quantum algorithm has low space and time complexity, demonstrating its memory and computational resources efficiency.

Estimation of timing characteristics in real-time computer systems using Petri nets

The work is devoted to the problem of determining the time characteristics of tasks in real-time systems, the success of which depends not only on their logical correctness, but also on the time for which they receive the result. Determining such time characteristics of the system at the design stage is a rather difficult problem. Its solution is currently based on the use of two main methods: theoretical calculations related to the calculation of the so-called feasibility criteria and modeling of the system's operation on models. Among the models, statistical models of mass service systems are the most widespread. However, in both the first and second options, it is impossible to obtain a guaranteed result, which significantly complicates the design process. Recently, it has been proposed to use the methods of researching models based on the use of the Petri net apparatus. The paper proposes a method for estimating the time characteristics of tasks in real-time systems by means of data analysis. Obtained by modeling the distribution of processor time between tasks according to the selected algorithms of the scheduler by using a model of the software system in the form of a Petri net. The paper proposes a method for estimating the time characteristics of tasks in real-time systems by means of data analysis. Obtained by modeling the distribution of processor time between tasks according to the selected algorithms of the scheduler by using a model of the software system in the form of a Petri net. The method guarantees obtaining the time characteristics of the tasks when choosing specific types of processor and scheduler, which is required to start the technical design of the real-time system. The use of the proposed mathematical model and a package of application programs allow, at the early stages of the development of a real-time system, to determine the real terms of tasks and choose the optimal option for the implementation of technical and lost support. The proposed mathematical models are based on determining the time characteristics of program execution by modeling the distribution of processor time between tasks, subject to the prior selection of planning algorithms and the characteristics of a complex of technical means. The research is based on the use of simulated statistical models and Petri net models, The use of the proposed tools allows you to significantly reduce the time of analysis of possible options for real-time system implementation, increases the quality of the project and significantly reduces the overall time and cost of the entire development. The paper examines in detail the process of modeling a multitasking computer system using a Petri net device. A concrete example shows the simulation of the operation of a complex of programs, including the development of simulation algorithms, the listing of the simulation program, and the analysis of the obtained results.

Exploring Sound Generation and Processing in Mechatronic Systems through Digital Signal Processing: A MATLAB-Based Investigation

Digital signal processing (DSP) encompasses various applications such as convolution, censoring, and filtering. These techniques find relevance in diverse fields, including computer games consoles, tone generation for mobile cellular devices, and theatrical performances. For computer engineers facing limited memory budgets in their devices, generating new sounds by convolving with existing sounds or noises becomes a significant challenge. The objective of this paper is to elucidate and demonstrate the generation of sounds through sound and recorded sound processing. These operations form the foundation of DSP, particularly digital filtering. Sound processing involves modifying prerecorded sound clips using different types of digital filters and processors. The entire process, including sound recording and processing, will be implemented and tested using MATLAB, the widely adopted technical computing software. This project aims to provide valuable archival material that complements the learning and expertise of computer engineering students and specialists.

State of the art of breeding, milking, and milk processing for the production of curdled milk and Wagashi Gassirè in Benin: Practices favoring the contamination of its dairy products

IntroductionThis study aimed to identify the factors favoring the contamination of raw cow's milk, curdled milk, and Wagashi Gassirè cheese during their production and preservation in order to develop strategies to improve their quality.MethodsA cross-sectional survey of 401 randomly selected stakeholders encompassing all levels of the dairy production chain in the Nikki and Dassa-Zoumé communes of Benin was conducted. The data obtained were analyzed using the SAS software for the calculation of frequencies and the R software for classifying the stakeholders based on the hygiene practices they adopted during the production and conservation of raw cow's milk, curdled milk, and Wagashi Gassirè.Results and discussionThe study identified three types of dairy farmers based on how they medically treated their cattle and implemented hygiene practices, including farmers who (1) relied on themselves or received help from veterinarians trained in animal husbandry and milking to monitor the animals on their farms; (2) relied only on veterinarians; and (3) relied only on themselves. The majority of these dairy farmers felt that hygienic milking practices were very restrictive and difficult to implement. In addition, three groups of Wagashi Gassirè producers were identified: (1) producers trained in good hygiene practices who did not boil or sundry the cheese; (2) producers lacking the infrastructure to protect from weather exposure who used all parts of Calotropis procera for colored Wagashi Gassirè production; and (3) producers who did not often filter the milk and boiled the Wagashi Gassirè in bags before immersion in simple water or whey. The sanitary quality of milk and milk products is influenced by the diverse handling practices employed by producers. These practices must be considered according to the types of farmers and processors when suggesting improved intervention policies.

Schedulability Analysis for Coscheduling Real-Time Tasks on Multiprocessors

The real-time coscheduling problem, where tasks may have multiple phases executing on different types of processors, is known to be hard. The (already hard) self-suspending task scheduling simplifies the coscheduling problem by assuming that the latency a task may experience on the other type of processors is naturally bounded, which is unfortunately not true in practice. In this article, we present a novel analysis technique, namely, the vertical view analysis, for analyzing the schedulability of coscheduling sporadic tasks under global earliest-deadline-first (GEDF) on a heterogeneous multiprocessor consisting of two types of processors. We derive both hard (no deadline miss) and soft (bounded response times) real-time utilization-based tests. To the best of our knowledge, these results are the first-of-its-kind for the coscheduling problem and may allow real-time schedulability analysis to be carried out on more practical scenarios under heterogeneous computing.

Priority queueing system with many types of requests and restricted processor sharing

A priority queueing model with many types of requests and restricted processor sharing is considered. A novel discipline of requests admission and service is proposed. This discipline assumes restriction of the bandwidth (capacity) of the server and the number of requests that can receive service in the system at the same time. This discipline is some kind of realistic hybrid of the traditional discipline of service in a multi-server system and the discipline of the limited processor sharing. The requests of the highest priority can push out from the service the low priority requests. Therefore, the important problem is fitting of the number of requests that can receive service at the same time to the bandwidth of the server. This problem is solved via construction and analysis of a multi-dimensional Markov chain describing operation of the system under any fixed set of the system parameters.

Insect-inspired AI for autonomous robots.

Autonomous robots are expected to perform a wide range of sophisticated tasks in complex, unknown environments. However, available onboard computing capabilities and algorithms represent a considerable obstacle to reaching higher levels of autonomy, especially as robots get smaller and the end of Moore's law approaches. Here, we argue that inspiration from insect intelligence is a promising alternative to classic methods in robotics for the artificial intelligence (AI) needed for the autonomy of small, mobile robots. The advantage of insect intelligence stems from its resource efficiency (or parsimony) especially in terms of power and mass. First, we discuss the main aspects of insect intelligence underlying this parsimony: embodiment, sensory-motor coordination, and swarming. Then, we take stock of where insect-inspired AI stands as an alternative to other approaches to important robotic tasks such as navigation and identify open challenges on the road to its more widespread adoption. Last, we reflect on the types of processors that are suitable for implementing insect-inspired AI, from more traditional ones such as microcontrollers and field-programmable gate arrays to unconventional neuromorphic processors. We argue that even for neuromorphic processors, one should not simply apply existing AI algorithms but exploit insights from natural insect intelligence to get maximally efficient AI for robot autonomy.

Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions

BackgroundThe efficiency of artificial intelligence as computer‐aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especially during interventions such as polypectomies. Those distracting CADe detections are often induced by the introduction of snares or biopsy forceps as the systems have not been trained for such situations. In addition, there are a significant number of non‐false but not relevant detections, since the polyp has already been previously detected. All these detections have the potential to disturb the examiner's work.ObjectivesDevelopment and evaluation of a convolutional neuronal network that recognizes instruments in the endoscopic image, suppresses distracting CADe detections, and reliably detects endoscopic interventions.MethodsA total of 580 different examination videos from 9 different centers using 4 different processor types were screened for instruments and represented the training dataset (519,856 images in total, 144,217 contained a visible instrument). The test dataset included 10 full‐colonoscopy videos that were analyzed for the recognition of visible instruments and detections by a commercially available CADe system (GI Genius, Medtronic).ResultsThe test dataset contained 153,623 images, 8.84% of those presented visible instruments (12 interventions, 19 instruments used). The convolutional neuronal network reached an overall accuracy in the detection of visible instruments of 98.59%. Sensitivity and specificity were 98.55% and 98.92%, respectively. A mean of 462.8 frames containing distracting CADe detections per colonoscopy were avoided using the convolutional neuronal network. This accounted for 95.6% of all distracting CADe detections.ConclusionsDetection of endoscopic instruments in colonoscopy using artificial intelligence technology is reliable and achieves high sensitivity and specificity. Accordingly, the new convolutional neuronal network could be used to reduce distracting CADe detections during endoscopic procedures. Thus, our study demonstrates the great potential of artificial intelligence technology beyond mucosal assessment.

Preoperative Imaging of Temporoparietal Scalp Thickness Predicts Off-the-Ear Sound Processor Retention in Cochlear Implants With Diametric Magnets.

To determine if temporoparietal scalp thickness assessed via preoperative imaging predicts retention events in patients who have cochlear implants with diametric magnets and various sound processor types. Retrospective chart and radiological review. Tertiary referral center. One hundred forty-three adult patients who have cochlear implants with diametric magnets. Skin flap thickness, retention events, body mass index (BMI), and magnet strength. Of 42 patients with the most recent generation off-the-ear sound processor (OTE2), 13 (31.0%) had retention events. Of patients with a temporoparietal scalp thickness less than 8 mm, all patients could ultimately retain the device, though one of 26 was noted to have tenuous retention. Of patients with 8 to 10 mm skin flaps, 3 of 6 (50%) could not retain the device, and with more than 10 mm skin flaps, 7 of 10 (70%) could not retain the device. In the more than 10 mm group, two additional patients could not either retain the device at initial activation or were noted to have tenuous retention. Of 124 patients with behind-the-ear (BTE) sound processors, only 2 (1.6%) could not retain the device at initial activation, and 3 (2.4%) exhibited tenuous retention after 3 months of device use. Results from the first generation off-the-ear sound processor (OTE1) are also reported. Temporoparietal scalp thickness measured by preoperative imaging is associated with processor retention for patients with the OTE2 sound processor and diametric magnets. All patients with less than 8 mm scalp thickness could retain the OTE2, while 50% of patients with 8 to 10 mm scalp thickness and 70% with more than 10 mm scalp thickness could not retain the device. Patients should be counseled regarding their sound processor choice and/or considered candidates for skin flap reduction or other intervention as indicated. Retention events with BTE processors are rare.

On the variance propagation of thermistor-based measurements with a digital temperature controller

Thermistor-based measurement systems at constant temperature have been widely used in multiple applications. In this type of hot-wire measurement applications, either analog circuits or digital processors can be used to regulate the thermistor temperature. The sampled-data control is an interesting alternative for temperature regulation because measurement signals are commonly handled by digital processors nowadays. However, the temperature control of Negative Temperature Coefficient (NTC) sensors present a nonlinear behavior in closed-loop operation. Furthermore, measurement variance depends on the temperature of the ambient and the dissipated power, but these relationships are nonlinear. This work proposes an approximated closed-loop propagation model for the output variance of an NTC-based measurement system at constant temperature. The thermistor temperature is regulated with a digital controller. Simulation and experimental results are presented in order to illustrate the benefits of the proposed model.