CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning.

Sensors' existence as a key component of Cyber-Physical Systems makes it susceptible to failures due to complex environments, low-quality production, and aging. When defective, sensors either stop communicating or convey incorrect information. These unsteady situations threaten the safety, economy, and reliability of a system. The objective of this study is to construct a lightweight machine learning-based fault detection and diagnostic system within the limited energy resources, memory, and computation of a Wireless Sensor Network (WSN). In this paper, a Context-Aware Fault Diagnostic (CAFD) scheme is proposed based on an ensemble learning algorithm called Extra-Trees. To evaluate the performance of the proposed scheme, a realistic WSN scenario composed of humidity and temperature sensor observations is replicated with extreme low-intensity faults. Six commonly occurring types of sensor fault are considered: drift, hard-over/bias, spike, erratic/precision degradation, stuck, and data-loss. The proposed CAFD scheme reveals the ability to accurately detect and diagnose low-intensity sensor faults in a timely manner. Moreover, the efficiency of the Extra-Trees algorithm in terms of diagnostic accuracy, F1-score, ROC-AUC, and training time is demonstrated by comparison with cutting-edge machine learning algorithms: a Support Vector Machine and a Neural Network.

Joint Relay Selection and Power Allocation through a Genetic Algorithm for Secure Cooperative Cognitive Radio Networks.

In cooperative cognitive radio networks (CCRNs), there has been growing demand of transmitting secondary user (SU) source information secretly to the corresponding SU destination with the aid of cooperative SU relays. Efficient power allocation (PA) among SU relays and multi-relay selection (MRS) are a critical problem for operating such networks whereas the interference to the primary user receiver is being kept below a tolerable level and the transmission power requirements of the secondary users are being satisfied. Subsequently, in the paper, we develop the problem to solve the optimal solution for PA and MRS in a collaborative amplify-and-forward-based CCRNs, in terms of maximizing the secrecy rate (SR) of the networks. It is found that the problem is a mixed integer programming problem and difficult to be solved. To cope with this difficulty, we propose a meta-heuristic genetic algorithm-based MRS and PA scheme to maximize the SR of the networks while satisfying transmission power and the interference requirements of the networks. Our simulation results reveal that the proposed scheme achieves near-optimal SR performance, compared to the exhaustive search scheme, and provides a significant SR improvement when compared with some conventional relay selection schemes with equal power allocation.

Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks.

Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

Solid-pseudopapillary tumor of the pancreas.

BACKGROUND: Solid-pseudopapillary tumor (SPT) of the pancreas is a low-grade malignancy, which has been infrequently observed in adolescent and young adult females since first report by Frantz in 1959. In this article, we describe our experience of 8 cases of SPT with the clinical features, diagnosis, treatments, and outcomes. METHODS: We retrospectively reviewed the medical records and images of 8 patients who underwent surgery for SPT between January 1995 and December 2004. RESULTS: Seven females and 1 male with the mean age of 29 years (range, 10 to 64) at presentation were identified. Three patients presented palpable abdominal mass, 2 with abdominal pain, and the remainder with no specific symptom. The mean diameter of the tumors was 7.9 cm (range, 4.0 to 10.0). Four were located in the tail, 3 in the body, and 1 in the head. Surgical procedure included distal pancreatectomy with/without splenectomy in 7 patients and Whipple operation in 1 with no surgical morbidity and mortality. All were alive without evidence of recurrence after mean follow-up of 26.4 months (range, 1 to 66). CONCLUSIONS: SPT of the pancreas is an unusual neoplasm and typically occurs in young females presenting well-demarcated pancreatic masses, which are amenable to cure by complete surgical resection.

A case of primary pancreatic non-Hodgkin's lymphoma.

Primary pancreatic lymphoma is rare, comprising 0.2-4.9% of all pancreatic malignancies and less than 1% of cases of non-Hodgkin's lymphoma. Many patients are diagnosed with lymphoma after radical resection. We report a rare presentation of diffuse large B cell lymphoma, appearing as a primary tumor of the pancreas. A 61-year old female was admitted to the hospital with the complaint of right upper abdominal pain. Computed tomography of the abdomen showed a well defined mass located at the head of the pancreas. A frozen section of pancreas, during laparotomy, revealed lymphoma. The patient received 6 cycles of chemotherapy and is currently in complete remission. This case underscores the importance of differentiating primary lymphoma from the more common adenocarcinoma of the pancreas as treatment and prognosis differ significantly. Primary pancreatic lymphoma should be considered in the differential diagnosis of pancreatic tumors and an attempt to obtain a tissue diagnosis is always necessary before proceeding to radical surgery, especially on young patients.

[The factors related to the prognosis of solitary hepatocellular carcinoma after radiofrequency ablation].

BACKGROUND/AIMS: Several risk factors, such as size and location, are related to local recurrence after radiofrequency ablation (RFA) in the treatment of hepatocellular carcinoma (HCC). The objectives of this study were to clarify factors related to prognosis. METHODS: From October 1999 to December 2002, we performed RFA for 107 consecutive patients with solitary HCC. We evaluated spiral computed tomography and serum alpha-fetoprotein level every 3 months after RFA. Seven possible factors for prognosis were analyzed using the Cox proportional hazards regression model: tumor size, tumor location, age, sex, etiology, platelet count, and Child-Pugh classification. Overall survival and disease free survival rate were estimated using the Kaplan-Meier method, and differences between two groups were compared using the log rank test. RESULTS: The Kaplan-Meier estimates of overall survival after radiofrequency ablation were 90.5% at 12 months, 67.4% at 24 months and 46.4% at 36 months and disease free survival were 71.4%, 46.7% and 20.9%, respectively. Using the Cox proportional hazards regression model, it was shown that with regard to overall survival and disease free survival, Child-Pugh classification (P=0.001, P=0.026) and platelet count (P<0.001, P=0.002) were statistically significant factors. The other factors did not have a statistically significant relationship to overall survival and disease free survival. CONCLUSIONS: The size and location known as local recurrence factors were not statistically significant with regard to survival and disease free survival. The Child-Pugh classification and platelet count, that reflect the liver function at the time of RFA, were significant factors for prognosis.

Clear cell hepatocellular carcinoma with spontaneous regression of primary and metastatic lesions.

The prognosis of advanced hepatocellular carcinoma (HCC) tends to be poor. Spontaneous regression of this lesion is extremely rare. In this report, we describe a case of HCC which spontaneously regressed along with a metastatic lesion of the chest wall. A huge HCC in the right lobe, the largest diameter of which was about 15 x 12 cm, developed in a 72-year-old man. He and his family refused further treatment. Three months after the diagnosis, metastasis to the chest wall was detected. We prescribed a painkiller for him in order to alleviate chest pain. Fourteen months after the diagnosis, the tumor size of the primary lesion was downsized to 3 x 4 cm in diameter. A biopsy taken from the chest wall proved to be clear cell HCC (CHCC). Since then, the metastatic lesion has also disappeared. Here, we report this unusual histologically proven CHCC with literature reviews.