Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency Block-Dependent Online Probabilistic Activation Control of Base Stations in Heterogeneous Networks

In this paper, we propose a novel frequency block-dependent online probabilistic activation control of base stations (BSs) in heterogeneous networks where low transmission-power pico-BSs are overlaid onto the coverage of a high-transmission-power macro-BS. The aim of the proposed method in this paper is to increase the system throughput within the system coverage using adaptive activation/deactivation of BSs depending on the location of the BSs and user terminals. By defining multiple frequency blocks in the overall system bandwidth and performing activation control on a per frequency block basis, we achieve an inter-cell interference coordination (ICIC) effect in addition to the overall reduction in inter-cell interference. The proposed method does not rely on complicated inter-BS cooperation. It uses inter-BS cooperation only to share the temporal system throughput observed for the entire system coverage. Based on the shared temporal system throughput information, each BS independently performs online activation control for the respective frequency blocks in a probabilistic manner. We also investigate an iterative algorithm to improve the convergence performance of the proposed method. Computer simulation results, in which the mobility of the user terminals is taken into account, show the effectiveness of the proposed method.
Diminished-1 Fermat Number Transform for Integer Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are a class of widely used deep artificial neural networks. However, training large CNNs to produce state-of-the-art results can take a long time. In addition, we need to reduce compute time of the inference stage for trained networks to make it accessible for real time applications. In order to achieve this, integer number formats INT8 and INT16 with reduced precision are being used to create Integer Convolutional Neural Networks (ICNNs) to allow them to be deployed on mobile devices or embedded systems. In this paper, Diminished-l Fermat Number Transform (DFNT), which refers to Fermat Number Transform (FNT) with diminished-l number representation, is proposed to accelerate ICNNs through algebraic properties of integer convolution. This is achieved by performing the convolution step as diminished -1 point-wise products between DFNT transformed feature maps, which can be reused multiple times in the calculation. Since representing and computing all the integers in the ring of integers modulo Fermat number $2^{b}+1$ for FNT requires $b+1$ bits, diminished-1 number representation is used to enable exact and efficient calculation. Using DFNT, integer convolution is implemented on a general purpose processor, showing speedup of 2–3x with typical parameter configurations and better scalability without any round-off error compared to the baseline.
Requirement of topoisomerase IV parC and parE genes for cell cycle progression and developmental regulation in Caulobacter crescentus

We have identified the parC and parE genes encoding DNA topoisomerase IV (Topo IV) in Caulobacter crescentus. We have also characterized the effect of conditional Topo IV mutations on cell division and morphology. Topo IV mutants of C. crescentus are unlike mutants of Escherichia coli and S. typhimurium, which form long filamentous cells that are defective in nucleoid segregation and divide frequently to produce anucleate cells. Topo IV mutants of C. crescentus are highly pinched at multiple sites (cell separation phenotype) and they do not divide to produce cells lacking DNA. These results suggest unique regulatory mechanisms coupling nucleoid partitioning and cell division in this aquatic bacterium. In addition, distinctive nucleoid‐partitioning defects are not apparent in C. crescentus Topo IV mutants as they are in E. coli and S. typhimurium. However, abnormal nucleoid segregation in parE mutant cells could be demonstrated in a genetic background containing a conditional mutation in the C. crescentus ftsA gene, an early cell division gene that is epistatic to parE for cell division and growth. We discuss these results in connection with the possible roles of C. crescentus Topo IV in the regulation of cell division, chromosome partitioning, and late events in polar morphogenesis. Although the ParC and ParE subunits of Topo IV are very similar in sequence to the GyrA and GyrB subunits of DNA gyrase, we have used DNA sequence analysis to identify a highly conserved ‘GyrA box’ sequence that is unique to the GyrA proteins and may serve as a hallmark of the GyrA protein family.
Cognitive Mechanism of Humor in Riddles: Examination of Relationship between Humor and Semantic Structure of Riddles

Riddles, such as "Why is A like B? Because they relate to C/C'," are a type of Japanese word game. The similarity between concepts in riddles reflect their semantic structures. In this research, the relationships between concept similarities and humor of the riddles were examined using the riddle-generation system on the Wikipedia corpus to cover enough concepts. The riddle-generation system provided riddles on the basis of similar concepts, which were estimated with word2vec using the Wikipedia corpus. The generated riddles were evaluated using the simulation results in order to clarify the relationships between concept similarities and humor. The experiment results suggested that riddles are funniest when the similarities between premises (A or B) and the reasons (C or C') are high and the similarity between the reasons themselves is low. Furthermore, an insufficient similarity between B and C' requires a sufficient amount of similarity between the reasons to elicit humor.
Securing OpenFlow Controller of Software-Defined Networks using Bayesian Network

Software-defined networking (SDN) is a new network architecture that has been proven to enhance network performance and reliability. OpenFlow is one of the most acceptable standards for building SDN solutions. Although OpenFlow promotes logically centralized control of network switches and routers in SDN environment, security is of major important for SDN deployment. The security of OpenFlow controller can be optionally implemented using Transport Layer Security (TLS). The aim of this research is to strengthen the security of the existing OpenFlow controller that can still be coupled with TLS implementation. Basic packet filtering was initially employed by inspecting the properties of each packet individually and then Bayesian network (BN) classifier was used to detect and filter unusual packet flows. Subsequently, this work was tested using Mininet as a network emulator for prototyping SDN controller functions on Ryu controller platform. The results show that the proposed work can significantly mitigate network attacks with small processing time and therefore help strengthen the security of the existing SDNs.
Feature Selection: Filter Methods Performance Challenges

Learning is the heart of intelligence. The focus in machine learning is to automate methods that achieve objectives, improve predictions or encourage informed behavior. Feature selection is a vital step in data analysis that often reduces dataset dimensionality by eliminating irrelevant and/or redundant attributes to simplify the learning process or improve outcomes’ quality. This research critically analyses different filter methods based on ranking procedures (Information Gain (IG), Chi-square (CHI), V-score, Fisher Score, mRMR, Va and ReliefF) and identifies possible challenges that arise. We particularly concentrate on how threshold determination can affect results of different filter methods based on ranked scores. We show that this issue is vital, especially in the era of big data in which users deal with attributes in the magnitudes of tens of thousands with only a limited number of instances.
Research on Pyramid Schemes Communication Network Based on Exponential Random Graph Models

As a kind of organized criminal organization, pyramid schemes organization has caused great economic losses to many countries. Social network analysis is a effective methods to study organized crime, and the exponential random graph model is a good tool to study the endogenous structure and network process of the organization. To the best of our knowledge, this work is the first time to use the exponential random graph model to study the communication network of a specific pyramid scheme. Results show that the communication network of pyramid schemes is sparse, and the core staff has less contact with the peripheral staff.
Extracting Topic Related Keywords by Backtracking CNN Based Text Classifier

In the last decades, many studies have been done to extract keywords from text and they show remarkable performance. Most of these studies use a rule-based methodology. They usually focus on Part of Speech(POS), collocations, co-occurrences and dependency of words. However, considering the topic of text is very important key for extracting keywords. Thus, in this paper, we proposed a keywords extracting method using Convolutional Neural Network(CNN) based text classifier which has sufficient information about the topic of text. Experimental results show that using topic related information in CNN text classifier model can improve the quality of keywords extraction. Also proposed method is advantageous in that it requires only a deep learning model differently from existing methods.
A TV White Space Wireless Broadband Prototype for Wireless Regional Area Network

In this paper, we present a prototype of the ARIB STD-T103 mode 1-based wireless broadband system for wireless regional area network (WRAN). The prototype is operated in a TV white space band, a VHF band of 170-202.5 MHz with a 5 MHz channel bandwidth. The ARIB STD-T103 mode 1 is based on the IEEE 802.16-2009 standard with OFDMA because of its easy implementation. The IEEE 802.16-2009-based system is originally expected to operate in microwave bands such as 2.5 GHz with 512 FFT-based OFDM in a 5 MHz channel. The ARIB STD-T103 mode 1-based system should tune the radio parameters of IEEE 802.16-2009 for VHF band propagation characteristics because many multipath waves with long delay are received in the VHF band. The ARIB STD-T103 mode 1 adopts OFDMA with 1024 FFT in a 5 MHz channel and convolutional Turbo coding to cope with long delay multipath environments such as the IEEE 802.22 Profile A model. The prototype is complied with the ARIB STD-T103 mode 1 and newly implement a channel estimation scheme for downlink to reduce the usage of memory in the mobile station as much as possible. This paper also evaluates the BER performance in AWGN and two multipath channel models and shows that the prototype achieved the required BER of 10-6 for all channel models.
Dialectical Behaviour Therapy: A Critique and Evaluation

The term “ borderline” first appeared in psychoanalytic literature earlier this century. It tended to refer to patients who were neither completely neurotic or psychotic but were still very disturbed (Goldstein, 1995). This term has evolved and presently “ borderline” generally refers to a severely disturbed personality (Ryle, 1997). The core features of the Borderline Personality Disorder are instability of mood, interpersonal relationships and identity (American Psychiatric Association, 1994). Suicide attempts are a common behavioural feature of this disorder.
Keyframe-Based Texture Mapping for RGBD Human Reconstruction

Realistic human model has a wide range of requirements in 3D content creation. A model with high-quality texture map can display human body surface details in low facets which could be toughly represented by geometric mesh. Image-based texture mapping suffers from discontinuities due to geometry inaccuracy, camera pose drifts, and illumination changes. In this paper, we propose a keyframe-based texture map generation method to obtain more desired texture mapping results. Our method firstly acquire the keyframes by performing a spatio-temporal sampling strategy, rather than just sampling keyframes according to time interval. Then, we apply an efficient patch-based optimization to the keyframes to make the texture data in different views alinged with each other. Finally, we generate a texture atlas from the aligned texture and the simplified mesh. Experimental results demonstrate that our method can get realistic human models with low facets and competitive details within short minutes.
Pharmacology and toxicology of europium chloride.

The pharmacological and toxicological properties of europium chloride have been studied. The intraperitoneal and oral LD 50′s were 550 mg. /Kg. and 5.0 Gm. /Kg. , respectively. Feeding various levels of the chemical for 12 weeks produced no effect on growth, the hemogram, or any internal organ. Transient ocular irritation with no permanent ocular damage was observed, but abraded skin showed extensive scar formation. Permanent nodule formation resulted from intradermal injection. Progressive depression was observed on all biological systems studied, and death was the result of cardiovascular collapse coupled with respiratory paralysis. Neither atropinization nor epinephrine injections could counteract the lethal effects.
An Improved Confidence Connected Liver Segmentation Method Based on Three Views of CT Images

To enhance the accuracy of liver segmentation, we present an improved confidence connected liver segmentation method, which combines the liver segmentation results obtained from three views is proposed. First, to reduce noise, an improved curvature anisotropic diffusion filter is applied, which simultaneously stores edge information. Second, seed points located in the liver are selected automatically using statistics and analysis of the liver intensity. We extract the liver contours from three views of computed tomography (CT) images using the confidence connected method and improve the contours by the cavity filling method. Finally, we combine the liver contours extracted from the coronal, sagittal, and cross section. In our experiments, clinical validation is performed using ten abdominal CT datasets. The results show that our proposed method can extract liver contours quickly and accurately, achieving an overall true positive rate (TPR) of 0.97. In addition, this method is useful for clinical diagnosis of liver disorders and virtual surgical planning.
Fictitious Flux and a Globally Stable Observer for Sensorless Control of Synchronous Reluctance Motors

The challenging problem of globally stable position and speed estimation of synchronous reluctance motors is solved with the proposed flux observer. Global stability is assured by the introduction of a new fictitious flux variable in the motor's model. Rotor position and speed are estimated from the fictitious flux using a vector phase-locked loop. Theoretical results are verified by simulation which shows stable estimation and good sensorless performances under various operating conditions.
Improved Grid-Side Current Control of LCL-Filtered Grid-Tied Inverters Under Weak Grid Conditions

Three-phase voltage source inverters are key parts to integrate renewable energy resources into the electrical grid. In order to achieve an acceptable attenuation of current harmonics in grid tied inverters and meet grid interconnection recommendations, an inductor-capacitor-inductor (LCL) type filter is commonly used as an interface between the inverter and the grid. However, this filter exhibits a resonant peak that should be properly damped to ensure system stability. Moreover, grid impedance variations, mainly under weak grid conditions, may shift the resonance frequency which compromises the controller design. This paper proposes a systematic approach to actively damp the LCL filter resonance using the notch filter-based control. An adaptive approach is also considered to improve the control performance under grid impedance variations. Computer simulations results are presented to demonstrate the effectiveness and robustness of the proposed control method.
Reduction of the Causes of Stock-Outs in Erp Supply Chain Management by Prioritization of the Causes

Enterprise resource planning (ERP) systems have a good reputation for automation and strength in the integration of business processes (BPs), therefore more and more organizations are adopting ERP systems. The City of Cape Town (CCT), is a metropolitan municipality in the Western Cape province in South Africa. Stock-outs remain a problem at The CCT, though an ERP system was implemented since 2002 to address stock-outs among other issues. The ERP provides insufficient information to link stock-outs to the causes. This makes it difficult to select the most appropriate solution to minimize the causes and number of stock-outs. Qualitative research methodology is applied to explore the possible reduction of the causes of stock-outs at CCT stores. Purposive sampling method is used on five different interviewee groups. Data was collected, using interviews via semi-structured questionnaires and the data were analyzed using thematic analysis. Results indicate that the top three, most contributing causes of stock-outs are policies and procedures, followed by ERP system issues, then training related issues.
Memory Trojan Attack on Neural Network Accelerators

Neural network accelerators are widely deployed in application systems for computer vision, speech recognition, and machine translation. Due to ubiquitous deployment of these systems, a strong incentive rises for adversaries to attack such artificial intelligence (AI) systems. Trojan is one of the most important attack models in hardware security domain. Hardware Trojans are malicious modifications to original ICs inserted by adversaries, which lead the system to malfunction after being triggered. The globalization of the semiconductor gives a chance for the adversary to conduct the hardware Trojan attacks.Previous works design Neural Network (NN) Trojans with access to the model, toolchain, and hardware platform. However, the threat model is impractical which hinders their real adoption. In this work, we propose a memory Trojan methodology without the help of toolchain manipulation and model parameter information. We first leverage the memory access patterns to identify the input image data. Then we propose a Trojan triggering method based on the dedicated input image other than the circuit events, which has better controllability. The triggering mechanism works well even with environment noise and preprocessing towards the original images. In the end, we implement and verify the effectiveness of accuracy degradation attack.
Paradoxical effects of learning the Morris water maze on adult hippocampal neurogenesis in mice may be explained by a combination of stress and physical activity

Studies in rats that assessed the relation of hippocampus‐dependent learning and adult hippocampal neurogenesis suggested a direct regulatory effect of learning on neurogenesis, whereas a similar study in mice had not found such causal link. We here report a substantial decrease of BrdU‐positive cells and other measures of adult hippocampal neurogenesis in mice trained in the hidden (HID) or cued version (VIS) of the Morris water maze as compared to untrained animals (CTR). Particularly, cells on advanced stages of neuronal development contributed to this decrease, whereas earlier progenitors (type 2 cells) were not diminished in HID, but were diminished in VIS as compared to CTR. The differential regulation of type 2 cells in HID and VIS may have been caused by a different degree of physical activity, given that a time‐yoked control group did not differ from HID, and type 2 cells reportedly constitute the proliferative dentate gyrus population that primarily responds to physical activity. The decrease of hippocampal neurogenesis by water maze training was reversible by pre‐exposing animals to the water maze prior to training, suggesting that stress associated with training may have caused the acute downregulation of adult neurogenesis. We propose that in mice the Morris water maze does not provide a pure enough learning stimulus to study the presumed effects of ‘learning’ on adult neurogenesis. In addition, however, our data show that physical activity that is intricately linked to many cognitive tasks in rodents might play an important role in explaining effects of learning on cellular hippocampal plasticity.
Effect of various tooth-whitening products on enamel microhardness.

OBJECTIVES The purpose of this in vitro study was to evaluate the effect of various tooth-whitening products containing carbamide peroxide (CP) or hydrogen peroxide (HP), on enamel microhardness. METHODS Enamel blocks were exposed to: Nite White ACP 10% CP (Group 2, n=10); Yotuel Patient 10% CP (Group 3, n=10); Opalescence PF 10% CP (Group 4, n=10); Opalescence PF 20% CP (Group 5, n=10); Opalescence Treswhite Supreme 10% HP (Group 6, n=10); Yotuel 10 Minutes 30% CP (Group 7, n=10); Opalescence Quick 45% CP (Group 8, n=10), Yotuel Special 35% HP (Group 9, n=10), Opalescence Boost 38% HP (Group 10, n=10) according to the instructions of the manufacturers. The control (Group 1, n=10) was enamel blocks kept in artificial saliva at 37 degrees C without any treatment. The microhardness values were obtained before exposure and after a 14-day treatment period. Specimens were kept in artificial saliva at 37 degrees C between treatments. Data were analysed using Kruskal-Wallis one-way ANOVA and Tukey-Kramer Multiple Comparison Test. Indent marks on the enamel blocks were also examined under the Scanning Electron Microscope. RESULTS All whitening products decreased enamel microhardness except group 10 but only Groups 2, 3, 4, 5 and 7 showed significant decrease in enamel microhardness as compared to the control group (p < 0.05). Groups 2, 3 and 7 differed significantly from all the other groups (p < 0.05). The highest damage was recorded for Group 2 (Nite White ACP 10% CP), which differed significantly from Groups 3 and 7. SEM images also showed damage to enamel. CONCLUSIONS All products tested in this study decreased enamel microhardness except Opalescence Boost 38% HP. The products containing carbamide peroxide were more damaging to enamel because of the longer application times. Nite White ACP 10% CP showed the highest reduction in enamel microhardness as compared to other products tested.
The 3D Edge Reconstruction from 2D Image by Using Correlation Based Algorithm

In computer numerical control machine tools, using machining simulation to prevent collision have become more popular due to higher machining speed. The 3D reconstruction of objects is one of the main goals for 3D machine vision is presented in this paper. In the stereo vision, a 2D edge feature detection algorithm designed by integration of vision base image processing which can generate a new straight line on the edges of the object. The matching comparison process is solved with the Normalized Cross Correlation (NCC) to obtain the results of a new straight line matching to find disparity from distance between feature points on plane. The disparity can be obtained from two cameras by overlapped two objects that show the different positions of two objects in horizontal using the principles of geometry of two cameras. The different position results can find the coordinates of 3D (x, y, z) to be generating the straight lines on edge of the 3D objects. This method is simply and easier in the computing process for the reconstruction of the object. The results obtain are presented with an effective and accurate model and can take results input into the 3D recognition process.