Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrological Modeling of an Ungauged River Basin Using SWAT Model for Water Resource Management Case of Kayanga River Upstream Niandouba Dam

Hydrological modeling of ungauged basins is important and imperative for policymakers and stakeholders in water management. The Kayanga river upstream from the Niandouba dam is subject to extreme pressure caused by natural and anthropogenic factors. The hydro system Niandouba Dam and Confluent Dam are used to providing water for the irrigated perimeters in Anambe. Since there is no data available to evaluate the water resources entering the Niandouba Dam, we used Soil and Water Assessment Tools (SWAT) to set up a hydrological model in the ungauged basin of Kayanga river upstream Niandouba dam. A regionalization approach has been used to predict the river discharge at Niandouba watershed upstream of the Niandouba dam. SWAT model has been calibrated from 01/01/2001 to 31/12/2001 and validated from 01/01/2002 to 31/12/2002, with a daily scale on the Koulountou watershed. During the calibration period, the criteria of goodness of fit are respectively 0.87 for Nash-Sutcliffe Efficiency coefficient (NSE), 0.87 for coefficient of determination (R2), -1.6% for Percent Bias (PBIAS) and 0.36 for Standard Deviation Ratio (RSR). In the validation period, we have found a Nash-Sutcliffe Efficiency coefficient (NSE) of 0.62, a coefficient of determination (R2) of 0.77, a Percent Bias (PBIAS) of +35.9%, Standard Deviation Ratio (RSR) of 0.62. These parameters have been used to generate flows at the entrance of the Niandouba Dam.
Porous Silicon Fabrication for MEMS Applications

We describe the use of porous silicon fabrication technique for fabricating non-manhattan structures in silicon using wet etching. The fabrication method is simple to set up, economical and produces smooth etched surface. A solid source diffusion of N++ in a P type wafer with low stress thermally grown silicon nitride is used as a masking layer. Comparison of porous silicon etches with wafers solid source diffusion and implanted diffusion is presented. The result show that areas where a solid source diffusion is used form an etch angle of 70-80°, however using an implanted diffusion the etch angle is closer to 90°. The selectivity of the etch during porous silicon fabrication using any of the above two as masking layer results in fabrication of high aspect ratio non-manhattan structures. These structures since are wet etched do not have surface roughness and can be used for optical applications.
Electrical Stimulation Therapy and Home Devices

Acupuncture Bone Growth Stimulators: Electrical (Invasive, Noninvasive), Ultrasound Diaphragmatic/Phrenic Nerve Stimulation Electric Stimulation for Pain, Swelling and Function in a Clinical Setting Extracorporeal Shock Wave Therapy (ESWT) for Musculoskeletal Conditions and Soft Tissue Wounds Gastric Pacing/Gastric Electrical Stimulation (GES) Headache and Occipital Neuralgia Treatment Injectable Bulking Agents for Urinary Conditions and Fecal Incontinence Omnibus Codes Plantar Fasciitis Treatments Sacral Nerve and Tibial Nerve Stimulation for Urinary Voiding Dysfunction, Fecal Incontinence and Constipation Speech Therapy Spinal Cord and Dorsal Root Ganglion Stimulation Transcranial Magnetic Stimulation Vagus Nerve Stimulation (VNS)
Housing Development, Local Land Conflicts and Sustainable Land-use Planning in Peri-urban Ghana

This paper examines the various ways local land conflicts affect sustainable land-use planning in peri-urban Ghana. In recent years, rapid urbanisation has resulted a high demand for customary lands for housing development in peri-urban areas in Ghana. Customary lands are continuously converted into housing uses; leading to eviction of indigenes from their farmlands. A mixed method approach was used to collect data from 40 participants from the research site, Aburaso. Purposive sampling technique was used to sample nine key informants while simple random sampling technique was employed to gather thirty-one individual household developers. The study found that dispossession of indigenes and poor accountability on the part of chiefs create contestations within royal family; land conflicts between chiefs and other clans in communities. The ultimate results are violence, death, poor land allocation and poor land-use planning with houses lacking portable water, proper sanitation and good access to roads.
Comparative Study of K-Means, Partitioning Around Medoids, Agglomerative Hierarchical, and DIANA Clustering Algorithms by Using Cancer Datasets

Clustering plays a particularly fundamental role in exploring data, creating predictions and to overcome the anomalies in the data. Clusters that contain parallel, identical characteristics in a dataset are grouped using reiterative algorithms. As the data in real world is rising day by day so the challenges of perceiving and interpreting the consequential mass of data, which often consists of millions of measurements are increased by the intricacy of a huge number of genes of biological networks. To addressing this challenge, we use clustering algorithms. In this study, we provided a comparative study of the four most popular clustering algorithms: K-Means, PAM, Agglomerative Hierarchical and DIANA and these are evaluated on eight real cancer (four Affymetrix and four cDNA) gene data and simulated data set. The comparative results based upon seven popular cluster validity indices: Average Silhouette Index, Corrected rand Index, Variation of Information, Dunn Index, Calinski-Harabasz Index, Separation Index, and Pearson Gamma. We determine that PAM is best for Affymetrix data set and DIANA is best for cDNA dataset among these four clustering algorithms. This study provides practical evaluation frameworks for accessing clustering results on gene expression cancer datasets.
Sequentially Greedy Unsupervised Learning of Gaussian Mixture Models by Means of A Binary Tree Structure

We propose an unsupervised learning algorithm for the estimation of the number of components and the parameters of a mixture model. It starts from a single mixture component covering the whole data set (therefore avoiding the ill-posed problem of the components’ initialization, saving also computational burden). Then, it incrementally splits that component during expectation maximization steps, thus exploiting the full space of solutions following a binary tree structure. After each component insertion it evaluates whether accepting this new solu-tion or discarding it according with the chosen information criterion. We show that the method is faster that state-of-the-art alternatives, is insensitive to initialization (deterministic initialization strategy), and has better data ﬁts in average. This is illustrated through a series of experiments, both with synthetic and real images.
A Study of Techniques in the Management of Simple Fistula in Ano

DOI: 10.21276/sjm.2018. 3.6. 12 Abstract: Fistula in Ano is a simple anorectal condition, however, has the potential to cause high morbidity. The usual line of surgical treatment for simple fistula in ano includes fistulotomy with marsupialization and fistulectomy. The present study was aimed to determine the overall outcomes after treatment of patients with fistulotomy with marsupialization and fistulectomy and compare the results in terms of post-operative complications and recurrences. Methods: The study involved 70 patients diagnosed with simple fistula in ano. Patients with morbid medical conditions and those diagnosed with complex fistulas were excluded from the study. The Clinical examination included perineal inspection, palpation, digital rectal examination and proctoscopic evaluation. The patients were then randomly divided into two groups. The group I patients underwent fistulectomy and the group II underwent fistulotomy with marsupialization. The patients were operated under general or regional anesthesia. The anorectal examination was done to verify the findings of the clinical examination. The patency of the tract was checked using the probe to the external opening. Seventy patients diagnosed with simple anal fistula were involved in the study. The mean distance of external fistula opening in group I was 2.6 ± 0.54 cms and the mean distance in group II was 2.5 ± 1.05. The duration of symptoms in group I and group II was 7.60 ± 2.9 and 8.85 ± 3.2 weeks respectively. The mean duration of surgery in group I was 12.5 ± 2.2, was 9.95 ± 1.25 in group II. Postoperative healing of the wounds was earlier in group II 4.06 ± 0.95 as compared to group I 5.15 ± 2.5. The mean VAS score was calculated on the 3 rd postoperative day in both the group of patients. In group I the mean VAS score was 2.25 and the mean VAS score in Group II was 2.25. No patient in the study developed the wound infection and none had other complications. Conclusions: Within the limitations of the present study it can be concluded that fistulotomy with marsupialization and fistulectomy are equally effective in terms of the outcomes of treatment of simple fistula in ano. Although fistulectomy requires longer post-operative healing and the mean VAS scores were higher in the fistulectomy group then compared to fistulotomy group. No recurrence and occurrences of complications were noted in both the groups.
Sampled Mean Shift for Fast Image Segmentation

The mean shift algorithm has been used successfully in image segmentation. However this class of algorithms tends to consume considerable amount of computation. In this paper we present a sampled version of the mean-shift (M-S) algorithm. Instead of processing the whole image, our method iterates over a subset of the image points to initialize a line search process for region boundary delimitation. To finalize the segmentation, we merge regions with partial overlay. We illustrate the effectiveness of our method with both synthetic and real images
Effect of 2, 4-dichlorophenoxyacetic acid on callus induction in wheat (Triticum aestivum L.) genotypes

Wheat is a member of family poaceae. Mature healthy seeds of four genotypes of wheat viz., PBW343, PBW373, RAJ 3765 and HD 2687 were inoculated on the MS media supplemented with 2, 4-D (2, 4-Dichlorophenoxy acetic acid). Four different combinations of 2, 4-D ranging from 5-8 mg L-1 was used for callus induction in four Indian varieties. Higher levels of 2,4-D were found to inhibit callus proliferation. Maximum callus induction was obtained in PBW343 (90.0%) at 6.0 mg L-1 2, 4-D followed by HD2687 (65.0%). Good embryoid production was apparent in third and fourth weeks of callus subculture. Average fresh weights of the calli for PBW 343 and HD2967 were 0.31 and 0.27 g per explant source, respectively.
Durable Top-K Instant-Stamped Temporal Records with User-Specified Scoring Functions

A way of finding interesting or exceptional records from instant-stamped temporal data is to consider their "durability, " or, intuitively speaking, how well they compare with other records that arrived earlier or later, and how long they retain their supremacy. For example, people are naturally fascinated by claims with long durability, such as: "On January 22, 2006, Kobe Bryant dropped 81 points against Toronto Raptors. Since then, this scoring record has yet to be broken. " In general, given a sequence of instant-stamped records, suppose that we can rank them by a user-specified scoring function f, which may consider multiple attributes of a record to compute a single score for ranking. This paper studies durable top-k queries, which find records whose scores were within top-k among those records within a "durability window" of given length, e.g., a 10-year window starting/ending at the timestamp of the record. The parameter k, the length of the durability window, and parameters of the scoring function (which capture user preference) can all be given at the query time. We illustrate why this problem formulation yields more meaningful answers in some practical situations than other similar types of queries considered previously. We propose new algorithms for solving this problem, and provide a comprehensive theoretical analysis on the complexities of the problem itself and of our algorithms. Our algorithms vastly outperform various baselines (by up to two orders of magnitude on real and synthetic datasets).
NEWS HUNTER: BUILDING AND MINING KNOWLEDGE GRAPHS FOR NEWSROOM SYSTEMS

Journalism is challenged by digitalisation and social media, resulting in lower subscription numbers and reduced advertising income. Information and communication techniques (ICT) offer new opportunities. We are exploring how social, open, and other data sources can be leveraged for journalistic purposes through techniques such as knowledge graphs, natural-language processing (NLP), and machine learning (ML). Our focus is on how these and other heterogeneous data sources and techniques can be combined into a flexible architecture that can evolve and grow to support the needs of future digital journalists. The paper presents the current state of our architecture and its instantiation as a prototype we have called News Hunter. Plans and possibilities for future work are also outlined.
Deep Learning Methods for EEG Signals Classification of Motor Imagery in BCI

EEG signals are obtained from an EEG device after recording the user's brain signals. EEG signals can be generated by the user after performing motor movements or imagery tasks. Motor Imagery (MI) is the task of imagining motor movements that resemble the original motor movements. Brain Computer Interface (BCI) bridges interactions between users and applications in performing tasks. Brain Computer Interface (BCI) Competition IV 2a was used in this study. A fully automated correction method of EOG artifacts in EEG recordings was applied in order to remove artifacts and Common Spatial Pattern (CSP) to get features that can distinguish motor imagery tasks. In this study, a comparative studies between two deep learning methods was explored, namely Deep Belief Network (DBN) and Long Short Term Memory (LSTM). Usability of both deep learning methods was evaluated using the BCI Competition IV-2a dataset. The experimental results of these two deep learning methods show average accuracy of 50.35% for DBN and 49.65% for LSTM.
A Survey over Low-Level Security Issues in Heavy Duty Vehicles

—This is the era of open architectures, ﬂeet management systems, remote support and other advanced features that can mean added value against competitors in heavy-duty vehicles industry. The need for security measures has emerged for In-Vehicle networks to avoid and prevent a number of issues, which become relevant with the increase of connectivity of such networks. A deep knowledge of the security problems, methodologies and possible solutions has been developed in the IT ﬁeld, but there are signiﬁcant differences in the application requirements and the network itself, when it comes to heavy-duty machines, speciﬁcally time-triggered communication and network throughput. Although researchers are overtaking network constrains with the recent research on the use of high-speed networks such as Ethernet instead of the classic CAN bus, security issues still remain a major constraint. The basic issues can be identiﬁed with an appropriate attacker model, which will be used to identify some security threats, proposing existing solutions and the challenges that they pose. In particular, in this paper we propose solutions for speciﬁc security threats, and compare their outcome both for the low-speed CAN and high-speed Ethernet networks, with emphasis on the authentication, integrity and encryption solutions.
Comparison of Three Radiation Dose Levels after EBVP Regimen in Favorable Supradiaphragmatic Clinical Stages (CS) I-II Hodgkin’s Lymphoma (HL): Preliminary Results of the EORTC-GELA H9-F Trial.

Preventing late toxicity has become the cornerstone in the management of HL as global results greatly improved regarding event-free (EFS) and overall survival (OS) rates. With this aim, the EORTC and GELA groups conducted a trial (H9-F) comparing three radiation doses in patients in complete remission (CR/CRu) after chemotherapy. Adult patients with supradiaphragmatic CS I-II HL and favorable features (age 20% of events). After 6 EBVP response rates were 50% CR, 26% CRu, 18% PR, 3% no change or progression, and 3% unspecified. Of the 591 CR/CRu patients, 13 (2%) were not randomized (6 refusals, 3 protocol violations, 4 causes unspecified). After a median follow-up of 51 months (range 14–81), 130 events (36 progressions, 91 relapses, 1 toxic death, 2 deaths of second cancer) were observed. At July 2005, the 4-year EFS and OS rates are as follows: Non-randomized patients experienced a significantly worse OS than did complete responders (P=0.0012). Relapses in nodal sites were more frequent in the no RT arm (35 in unirradiated sites) than in RT arms (6 + 10 in irradiated sites). 15 patients have died, 10 of progressive disease, 2 of treatment-related complication, 1 of intercurrent disease and 2 of second cancer (1 AML, 1 NHL). In favorable early stage HL patients who achieve CR(u) after 6 cycles of EBVP, omission of IF-RT leads to an unacceptable failure rate; In contrast, with the current follow-up, IF-RT 20 Gy provides results equivalent to those of IF-RT 36 Gy.
Thermomechanical Analysis of Laser-generated Ultrasonics in Thin Structures by Finite Element Method Thermomechanical Analysis of Laser-generated Ultrasonics in Thin Structures by Finite Element Method Advisor: Professor Jung-Wuk Hong by

Ultrasonic guided waves have been widely utilized for the structural health monitoring (SHM) of structural components such as plates and pipes; Lamb wave as one of means for nondestructive testing and evaluation has emerged to provide a new way for the inspection of thin structures. In particular, the noncontact excitation of the pipe surfaces using laser pulses has shown several advantages in experiments by eliminating the bonding process of the dielectric patches on the curved surfaces and the complicated interpretation of the temperature effect on the bonding layers. However, the numerical simulation of the methodology requires thermo-mechanical coupling and large-scale computation. Therefore, the numerical efficiency of the spatial partitioning by deploying thermomechanical elements and mechanical elements is investigated. The formation and propagation of the guided waves are also represented numerically. A multi-scale simulation technique for three-dimensional wave propagation through pipe-like structures is developed considering the noncontact excitation by a short duration laser pulse. Using this technique, the displacement fields in pipes, both with and without a notch, are calculated and analyzed. In particular, the heat flux is applied to a micro-scale model, and then the temperature profile is obtained. The obtained temperature profile is imposed as the thermal boundary of the macro-scale global model. By applying the temperature profile to an intact pipe, the displacement fields are compared with experimental results in a literature. On the other hand, it is found that the existence of a notch makes effects on the propagation of waves. Therefore, the interaction causes some deviation of the displacement fields. The dissimilarity in the displacement fields with different notch depths is investigated using a statistical signal processing technique. Based on the investigation, a damage detection technique that evaluates the existence of a notch in a pipe is proposed.
Scene Depth Estimation Based on Odometry and Image Data

In this work, we propose a depth estimation system based on image sequence and odometry information. The key idea is that depth estimation is decoupled from pose estimation. Such approach results in multipurpose system applicable on different robot platforms and for different depth estimation related problems. Our implementation uses various filtration techniques, operates real-time and provides appropriate results. Although the system was aimed at and tested on drone platform, it can be well used on any other type of autonomous vehicle that provides odometry information and video output.
Identification of key protein-coding genes in lung adenocarcinomas based on bioinformatic analysis

Background Lung cancer is one of the most common cancers and the primary cause of cancer-related deaths in the world. The 5-year survival of lung cancer patients is lower than 15%. As a common subtype of lung cancer, lung adenocarcinoma still has a high morbidity and mortality, although many strategies have been made, such as surgical operation, chemotherapy, targeted therapy. The use of gene expression microarray has provided a feasible and effective approach for the study on lung cancer. However, the biomarkers and potential therapeutic targets of lung adenocarcinomas are still not completely identified. Our study is aimed to find biomarkers and therapeutic targets of lung adenocarcinomas by identifying the key protein-coding gene in lung adenocarcinomas by bioinformatical approaches. Methods We selected and obtained messenger RNA microarray datasets from Gene Expression Omnibus database to identify differentially expressed genes between lung adenocarcinomas and normal lung tissue. The differentially expressed genes were clarified by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the protein-protein interaction (PPI) network and statistical analyses. Subsequently, quantitative real-time PCR was used to verify the results of bioinformatic analysis. Results We obtained 1,264, 896 and 408 differentially expressed genes from GSE32863, GSE43458 and GSE63459, respectively. The 242 common differentially expressed genes in three datasets were related to cell adhesion molecules, ECM-receptor interaction, leukocyte transendothelial migration according to KEGG analysis. GO analysis showed that these common differentially expressed genes were enriched in tumor-related functions. ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T and KIAA0101 have the strongest protein-protein interaction relationships based on protein-protein interaction networks. Survival analysis showed that these nine genes were closely related to the survival of lung adenocarcinomas. The further qRT-PCR assays indicated that seven key genes (ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T) display differential profile between clinical lung adenocarcinoma specimens and their matched normal tissues. Conclusions ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T may be key protein coding genes in lung adenocarcinoma, and deserve further study to verify their feasibility and effectiveness as biomarkers and therapeutic targets for lung adenocarcinomas.
PESARO 2013 Proceedings

The Safe Control Systems (SaCS) method is a pattern-based method supporting the development of conceptual designs for safety critical systems. A pattern language offers support for the method by six different kinds of basic patterns, operators for combining patterns, and a graphical notation for visualising a pattern composition. Intended users of SaCS are system developers, safety engineers and HW/SW engineers. The method has so far been applied in two cases within different industrial domains. This paper demonstrates and presents experiences from the application of SaCS within the railway domain. We consider an interlocking system that controls the appliances of a railway station. We argue that SaCS effectively supports the establishment of requirements, a design satisfying the requirements, and an outline of a safety demonstration for the design. Keywords-conceptual design; pattern language; development processes; safety;