Deep learning control for digital feedback systems: Improved performance with robustness against parameter change

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, such as sensor networks. The promising results of robustness against parameter changes are calling for future research in the direction of robust DL control

Deep learning for robust adaptive inverse control of nonlinear dynamic systems: Improved settling time with an autoencoder

An adaptive deep neural network is used in an inverse system identification setting to approximate the inverse of a nonlinear plant with the aim of constituting the plant controller by copying to the latter the weights and architecture of the converging deep neural network. This deep learning (DL) approach to the adaptive inverse control (AIC) problem is shown to outperform the adaptive filtering techniques and algorithms normally used in adaptive control, especially when in nonlinear plants. The deeper the controller, the better the inverse function approximation, provided that the nonlinear plant has an inverse and that this inverse can be approximated. Simulation results prove the feasibility of this DL-based adaptive inverse control scheme. The DL-based AIC system is robust to nonlinear plant parameter changes in that the plant output reassumes the value of the reference signal considerably faster than with the adaptive filter counterpart of the deep neural network. The settling and rise times of the step response are shown to improve in the DL-based AIC system

Comparison of Clinico-Pathological Presentations of Triple-Negative versus Triple-Positive and HER2 Iraqi Breast Cancer Patients

BACKGROUND: Breast cancer remains the most common malignancy among the Iraqi population. Affected patients exhibit different clinical behaviours according to the molecular subtypes of the tumour. AIM: To identify the clinical and pathological presentations of the Iraqi breast cancer subtypes identified by Estrogen receptors (ER), Progesterone receptors (PR) and HER2 expressions. PATIENTS AND METHODS: The present study comprised 486 Iraqi female patients diagnosed with breast cancer. ER, PR and HER2 contents of the primary tumours were assessed through immunohistochemical staining; classifying the patients into five different groups: Triple Negative (ER/PR negative/HER2 negative), Triple Positive (ER/PR positive/HER2 positive), Luminal A (ER/PR positive/HER2 negative), HER2 enriched ((ER/PR negative/HER2 positive) and all other subtypes. RESULTS: The major registered subtype was the Luminal A which was encountered in 230 patients (47.3%), followed by the Triple Negative (14.6%), Triple Positive (13.6%) and HER2 Enriched (11.5%). Patients exhibiting the Triple Negative subtype were significantly younger than the rest of the groups and presented with larger size tumours. A significant difference in the distribution of the breast cancer stages was displayed (p < 0.05); the most advanced were noted among those with HER2 enriched tumours who exhibited the highest frequency of poorly differentiated carcinomas and lymph node involvement. CONCLUSION: The most significant variations in the clinicopathological presentations were observed in the age and clinical stage of the patients at diagnosis. Adoption of breast cancer molecular subtype classification in countries with limited resources could serve as a valuable prognostic marker in the management of aggressive forms of the disease

Correlation between Breast Self-Examination Practices and Demographic Characteristics, Risk Factors and Clinical Stage of Breast Cancer among Iraqi Patients

BACKGROUND: Breast Cancer (BC) is the most common cancer and the leading cause of cancer death among women globally. The disease can be cured with limited resources if detected early. Breast self-examination (BSE) is considered a cost-effective feasible approach for early detection of that cancer in developing countries. AIM: To determine the correlation between BSE performance and demographic characteristics, risk factors and clinical stage of BC among Iraqi patients. METHODS: This retrospective study included a total of 409 female patients diagnosed with BC at the Referral Training Center for Early Detection of Breast Cancer and the National Cancer Research Center in Baghdad. The studied variables included the age of the patient, occupation, marital and educational status, parity, history of lactation, contraceptive pill intake, family history of cancer and the clinical stage of the disease. RESULTS: Our findings revealed that the most important predictors for practicing BSE was family history of BC or any other cancers (OR = 3.87, P = 0.018) followed by being a governmental employee (OR = 1.87, P = 0.024), history of contraceptive use (OR = 1.80, P = 0.011) and the high level of education (OR = 1.73, P = 0.004). On the other hand, there was no significant correlation between the practice of BSE and the BC stage at the time of presentation. CONCLUSION: There is a relatively poor practice of BSE among Iraqi patients diagnosed with BC. It is mandatory to foster the national cancer control strategies that focus on raising the level of awareness among the community through public education as a major approach to the early detection of cancer in Iraq

ANALISIS DAMPAK PARKIR TERHADAP KINERJA LALU LINTAS DI RUAS JALAN SEKITAR MALL MATAHARI KOTA PONTIANAK

Mall Matahari merupakan pertokoan yang cukup lama sehingga ketersediaan ruang parkir tidak terlalu direncanakan. Permasalahan kemacetan dikarenakan parkir di badan jalan sering terjadi dan tingkat aktivitas perekonomian juga tinggi, maka peneliti melakukan penelitian yang bertujuan menganalisa kebutuhan parkir, kinerja lalu lintas, dampak parkir terhadap lalu lintas, dan mencari upaya pengendalian parkir. Metodologi penelitan dengan cara survei lapangan yang dilakukan selama 3 hari dan data sekunder untuk menganalisa volume kendaraan, hambatan samping, karakteristik lalu lintas dan kapasitas. Dalam pengolahan data menggunakan PKJI 2014. Hasil pengolahan data diperoleh total kebutuhan ruang parkir di basement Mall Setelah di akumulasikan semua ruas jalan di Sekitar Mall adalah 17 SRP. Volume lalu lintas didapatkan nilai volume kendaraan tertinggi di Jl. AR. Hakim terjadi pada hari sabtu pukul 13.00-14.00 WIB dengan volume kendaraan adalah 585 SKR/jam, Jl. Jend. Urip hari senin pukul 11.00-12.00 WIB adalah 1605 SKR/jam, dan Jl. Pattimura hari minggu pukul 20.00-21.00 WIB adalah 1619 SKR/jam. Hasil analisis dampak parkir terhadap kinerja lalu lintas terlihat aktivitas parkir saat kondisi tanpa parkir lebih baik dibanding kondisi eksisting dengan rata-rata hasil ITP nya C. Hasil PKJI dan simulasi VISSIM didapat hasil yang sama dan dapat digunakan untuk mencari alternatif pengendalian parkir

Experimental investigation of modified solar still productivity under variable climatic conditions

Conversion of untreated water into drinking water using solar distillation technology can be considered as the most viable methods in the dry climate regions and remote areas. The productivity of solar stills influences by various conditions such as design, operational and environmental conditions. The current paper includes a practical investigation of the effects the climatic conditions on the fresh water production from modified single-slope solar still in Russia. Results analysis showed that the mechanism of heat transfer and mass transfer within the solar still depend on environmental parameters. The heat transfer coefficients have been gradually increased from the early morning after 08:00 am and reached the highest value at the noon then decrease gradually afternoon to reach the lowest value at 20:00 pm. The maximum value of coefficient of heat transfer by evaporation found to be 12.1 W/m2. K at 17:00 pm on 19.06.2019, then 9.9 W/m2. K at 17:00 pm on 18.06.2019, and 2 W/m2. K at 18:00 pm on 17.06.2019. Therefore, a noticeable improvement in the fresh water productivity from solar still has been observed with increasing solar radiation intensity, ambient temperature and decreasing relative humidity. The amount of production during a cloudy day was 287 ml/m2, 620 ml/m2 for a partial cloudy day and 950 ml/m2 during a sunny day. © 2020 WITPress. All rights reserved

Deformation behavior of flexible pavements by finite element simulation

Flexible pavement is usually designed based on certain axle load limits and climatic conditions. The Iraqi code has specified certain load limits per each axle type that should not be exceeded. However, many trucks violate these limits by carrying additional weights to decrease the transportation cost. These overweight trucks cause severe deterioration to the pavement and thus reduce its life. The Iraqi authorities generally charges the violating trucks a penalty based on their weights. This penalty could be very small compared to the damage occurring to the pavement based on these over weights. Also, some trucks may carry huge weights that the pavement may not support, so unloading such trucks could be a suitable solution rather than paying few amounts of money and deteriorating the pavement. The study aims at studying the effect of axle load increase, and the variation in pavement moduli, on the overall pavement life. It also aims to estimate the overweight truck limits that could be penalized or unloaded. The research uses the ABAQUS software conditions to estimate the tensile strains occurring under the asphalt concrete (AC) layer and the compressive strains above the subgrade surface. These computed strains are incorporated in the fatigue cracking and rutting models to estimate the pavement life for different axle weights. Results showed that violating trucks should be unloaded when their weights exceed certain limits