Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrusion Detection System Performance Enhancement Using Dynamic Agent Aggregation and Cloud Based Log Analysis

Intrusion detection is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of computer security policies, acceptable use policies, or standard security practices. An intrusion detection system (IDS) monitors network traffic and monitors for suspicious activity and alerts the system or network administrator. It identifies unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators. Intrusion detection systems (IDS) are essential components in a secure network environment, allowing for early detection of malicious activities and attacks. By employing information provided by IDS, it is possible to apply appropriate countermeasures and mitigate attacks that would otherwise seriously undermine network security. However, current high volumes of network traffic overwhelm most IDS techniques requiring new approaches that are able to handle huge volume of log and packet analysis while still maintaining high throughput. Hadoop, an open-source computing platform of MapReduce and a distributed file system, has become a popular infrastructure for massive data analytics because it facilitates scalable data processing and storage services on a distributed computing system consisting of commodity hardware. The proposed architecture is able to efficiently handle large volumes of collected data and consequent high processing loads using Hadoop, MapReduce and cloud computing infrastructure. The main focus of the paper is to enhance the throughput and scalability of the IDS Log analysis.
We need mutual aid too: group work instructors helping each other navigate online teaching

ABSTRACT The introduction of COVID-19 disrupted almost every facet of global societies, including institutions of higher education. With limited time to prepare for the emergent shift to virtual instruction, few educators had the time or emotional energy to invest in course redesign to meet established standards of quality online education. Strained by lack of guidance from their institutions and limited confidence in teaching social group work virtually, twelve group work educators initially participated in a weekly mutual aid group of peer members sponsored by the International Association for Social Work with Groups. This paper describes the evolution of a peer-facilitated, international, mutual aid group for group work educators making the transition to an online format – its conception, formation, purpose, structure, facilitation, and process. The authors address the personal experiences of all members, and place the group into a theoretical context.
Screening of phytochemicals as potential anti-breast cancer agents targeting HER2: an in-silico approach

Abstract Breast cancer is the most common cancer among women around the world. Human Epidermal growth factor Receptor-2 (HER2) is a membrane tyrosine kinase overexpressed in 30% of human breast cancers; thus, it serves as an important drug target. Currently available HER2 inhibitor lapatinib targets the ATP binding site of the cytoplasmic kinase domain, blocking autophosphorylation and activation of HER-2. However, it causes side effects like diarrhea, nausea, rash and possible liver toxicity. As phytochemicals have fewer side effects and are relatively affordable, they offer an effective alternative. Hence, we aimed to identify potential phytochemicals that could act as HER2 inhibitors employing computational methods such as molecular docking, molecular dynamic simulation, and ADMET prediction. Out of 1500 phytochemicals docked to the ATP binding site of the HER2 kinase domain, luxenchalcone, rhinacanthin Q, subtrifloralacton D, and 7,7″-dimethyllanaraflavone exhibited higher binding affinity than the reference inhibitor and satisfied the Lipinski’s rule of five. Analysis of molecular dynamics simulation trajectory showed that Rhinacanthin Q, subtrifloralacton D, and 7,7″-dimethyllanaraflavone formed a stable and compact complex without vast conformational fluctuations. MM/PBSA binding free energy analysis revealed that Rhinacanthin Q, subtrifloralacton D, and 7,7″-dimethyllanaraflavone have high binding affinity to HER2. Therefore, Rhinacanthin Q, subtrifloralacton D, and 7,7″-dimethyllanaraflavone could be potential bioactive molecules to act as inhibitor of HER2 protein. Eventually, experimental studies are needed to evaluate the potentials of these phytochemicals further. The development of drug for HER2 positive breast cancer could be accelerated with the findings of our research. Communicated by Ramaswamy H. Sarma
Designing a positioning system for finding things and people indoors

Despite extraordinary advances in Global Positioning System (GPS) technology, millions of square meters of indoor space are out of reach of Navstar satellites. Their signals, originating high above the Earth, are not designed to penetrate most construction materials, and no amount of technical wizardry is likely to help. So the greater part of the world's commerce, being conducted indoors, cannot be followed by GPS satellites. Here, the authors describe how tracking people and assets indoors has now moved from the realm of science fiction to reality, thanks to a radiofrequency identification technique now being introduced to the market.
Overcoming the liability of distance? An exploratory study of the associations between social networks, sense of community and spatial colocation

Purpose This study aims to examine the associations of social networks with the sense of community (SOC) construct and spatial colocation or having an office. The study site was an institute for health-care policy research formed in 2011 by bringing together scientists from more than 20 different university units. Only 30% of the scientists were had an office or physical presence at the institute. Therefore, the institute was an ideal site to examine whether SOC was correlated with different dimensions of network position – connectedness, reachability and brokerage – even when the authors account for the lack of spatial colocation for the off-site scientists. Design/methodology/approach A two-part (sociometric and workplace) internet survey instrument was administered in 2014 to the institute’s population of 411 individuals. The sociometric data were used to create an undirected interaction network and the following dependent variables (DVs) or network centralities: normalized degree to measure connectedness; average reciprocal distance to capture reachability; and normalized betweenness to proxy brokerage. Separate node-level network regressions were then run with random permutations (N = 10,000) and listwise deletion for each of the DVs with SOC and spatial colocation as the independent variables, and variables that controlled for gender, organizational affiliation and job category. Findings SOC and spatial colocation are both positively and significantly correlated with network connectedness and reachability. The results suggest that both SOC and spatial colocation have a larger impact on reachability than connectedness. However, neither SOC nor spatial colocation are significantly associated with network brokerage. Finally, the findings show that SOC and spatial colocation are more reliable predictors of network connectedness and reachability than are key individual- and unit-level control variables, specifically the individual’s sex, job category and organizational affiliation. The controls were not significantly associated with any of the three network centralities, namely, connectedness, reachability and brokerage. Originality/value This exploratory study used social network analysis and node-level network regressions to examine the associations from SOC and spatial colocation to dimensions of network position. SOC is positively and significantly associated with network connectedness and reachability, suggesting that SOC is an important consideration when individuals are disadvantaged from the absence of spatial colocation. The findings have implications for work in the context of the COVID-19 pandemic as they imply that interventions based on the SOC construct could potentially lessen the negative effects of remote work on workplace social networks due to factors such as the reduction of social contacts.
Removing the problem of locking not good in assembly of lever combination switch using continuous improvement process

Company Mindarika had reported poor quality of particular products in the assembly department which results in increasing cost, lead time, and customer complaints. The purpose of this study is to help the company Mindarika to improve the product quality and to manage the data for a continuous improvement plan by using continuous process improvement and the quality control techniques. This research paper is related with some modifications in the setting of hand press installed for locking the two plates of lever combination switch during its assembly. Methods and procedures of this study include a review of literature relevant to continuous improvement, quality control techniques, root cause analysis, seven tools of quality and assembly process of a specific automotive product (lever combination switch). After the causes of defects were identified, solutions and procedures were recommended to the company to eliminate defects in the assembly process of lever combination switch.
Active sound design for a passenger car based on adaptive order filter

The paper presents an adaptive order filter for the sound design of a passenger car. The engine speed is calculated by using the pulse signal detected at engine speed sensor such as cam shaft position sensor (CSPS) or engine ignition position sensor (EIPS). Nowadays, the pulse signal of engine speed is delivered to the engine management control unit (ECU) system. The ECU supplies the engine speed data to the display throughout a high speed gateway. The ANC system can also use this data for the generation of reference signal. Most of reference signals used for the noise control of an engine are the sine wave at the instant frequency (rpm/60). This sine wave is discretely changed with the increment of engine speed but not continuous. Therefore, the ANC system using this reference cannot work when the engine speed is changed rapidly form 1000rpm to 6000rpm but work well at the fixed rpm. In this paper new adaptive order filter (AOF) for the ANC system of interior noise of a car is proposed. The new algorism uses the continuous reference signal instead of the sine wave. This ANC system is also applied for the active sound design (ASD). The AOF is very excellent algorithm for the ASD of a vehicle.
Why and How to Construct a Device for Hail Simulation

Hail characterization is necessary for generating models to protect people and their goods. Designing an electronic characterization system requires reproducing hail events. The objective of this article is to present a design proposal of a device for hail simulation based on the theory of energy matching. The simulator uses steel balls in place of hailstones. It can be loaded with up to 14 balls of sizes between 0.5 cm to 3.0 cm, which can be either dropped one by one or in pairs. If dropped in pairs, the distance between them can be regulated, as well as the delay. In this paper, the importance of having such a device is explained and several experiments to be conducted by using it in order to design a hail sensor are described.
The effect of exposure to coherence relations on its processing and comprehension: Exploring Chilean primary school students’ performance

10.4067/S0718-09342021000301026 Abstract Previous corpus-based studies (Ibáñez, Moncada & Cárcamo, 2019) have identified the most and the least frequent coherence relations in Chilean primary school textbooks. Based on these findings, in this study, we explored the effect of exposure to coherence relations on their processing and comprehension. We expected the most frequent coherence relations in school textbooks to be more easily processed and better comprehended than the least frequent ones. Our expectation is explained by integrating the Language Experience (LE) hypothesis (Nippold & Taylor, 2002) and the Schematic Structural Expectations (SSE) hypothesis (Mulder, 2008). A self-paced reading experiment with a within-subjects design and cumulative window paradigm was carried out. One hundred and thirty-eight participants (12-14 years old), attending Chilean schools participated in the experiment. Each of them read 30 experimental items in two different sessions. Results revealed, in the first place, low levels of reading comprehension achievement. General results also showed that, although participants read the most frequent coherence relations slower than the least frequent ones, they comprehended them better. Analysis showed different patterns depending on the subject, which demonstrated that our expectations were partially
Personalizing Dual-Target Cortical Stimulation with Bayesian Parameter Optimization Successfully Treats Central Post-Stroke Pain: A Case Report

Central pain disorders, such as central post-stroke pain, remain clinically challenging to treat, despite many decades of pharmacological advances and the evolution of neuromodulation. For treatment refractory cases, previous studies have highlighted some benefits of cortical stimulation. Recent advances in new targets for pain and the optimization of neuromodulation encouraged our group to develop a dual cortical target approach paired with Bayesian optimization to provide a personalized treatment. Here, we present a case report of a woman who developed left-sided facial pain after multiple thalamic strokes. All previous pharmacologic and interventional treatments failed to mitigate the pain, leaving her incapacitated due to pain and medication side effects. She subsequently underwent a single burr hole for placement of motor cortex (M1) and dorsolateral prefrontal cortex (dlPFC) paddles for stimulation with externalization. By using Bayesian optimization to find optimal stimulation parameters and stimulation sites, we were able to reduce pain from an 8.5/10 to a 0/10 during a 5-day inpatient stay, with pain staying at or below a 2/10 one-month post-procedure. We found optimal treatment to be simultaneous stimulation of M1 and dlPFC without any evidence of seizure induction. In addition, we found no worsening in cognitive performance during a working memory task with dlPFC stimulation. This personalized approach using Bayesian optimization may provide a new foundation for treating central pain and other functional disorders through systematic evaluation of stimulation parameters.
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Single-phase materials with mixed ionic and electronic conductivity underpin multiple solid-state electrochemical devices as promising electrodes. In particular, triple-conducting oxides that carry protons, oxygen ions, and electron holes simultaneously have ushered in a breakthrough in improving the performance of ceramic fuel cells, but insuﬃcient electrochemical activity on their surface remains a challenge with regard to the development of related technologies. Here, we present a novel methodology that spontaneously yields transition metal nanocatalysts well dispersed on triple-conducting oxide surfaces realized by simply supplying water vapor with a room-temperature bubbler. The central idea underlying this strategy is the hydrogenation reaction that occurs in protonic ceramics containing redox-active transition metals and the subsequent selective surface phase decomposition. As a case study, Ag-substituted BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3 (cid:2) d is chosen to exemplify the markedly enhanced electrode performance in a fuel cell. The water vapor generated during the operation induces the precipitation of Ag nanoparticles and significantly lowers the electrode resistance to a record level ( e.g. , 1.20 W cm (cid:2) 2 at 650 1 C). These observations suggest a new design direction for oxide-supported catalysts with multiple charge carriers.
Creating Successful Process Improvement Programs: The Roles of Consultant and Industry

This study finds that Fortune 500 companies implement expensive process improvement programs only to often abandon them in the long run due to dismal performance, resulting in a waste of the resources used to implement the programs. To prevent this waste, this study develops an implementation model that promotes program sustainability for the long term. Using a technique called Learning by Doing, this model guides the implementation of process-improvement programs. Using a combination of empirical studies and four action-research field studies, this model connects the research on process improvement, Learning by Doing, and consultancy to support program sustainability.
Smart‐Bogie: Semi‐Active Lateral Control of Railway Vehicles

The topic of this paper is the design and analysis of a control system for the lateral movement of the carbody in a train. The control system is implemented via semi‐active electro‐hydraulic dampers located on the secondary‐suspension that links the bogie to the structure of the carbody of the train. The entire design procedure is outlined: the semi‐active damper is accurately modeled; using the actuator model, the control strategies are implemented and tuned on a vehicle simulator; the best control strategies then are implemented and tested on a realistic laboratory test‐bench, which accurately reproduces the lateral dynamics of a train. A wide range of semi‐active control strategies is tested. Among them, the best performing and most efficient is a recently‐proposed strategy which requires only a single sensor located cabin‐side.
Exercise Referral Instructors’ Perspectives on Supporting and Motivating Participants to Uptake, Attend and Adhere to Exercise Prescription: A Qualitative Study

Exercise referral schemes are designed to support people with non-communicable diseases to increase their levels of exercise to improve health. However, uptake and attendance are low. This exploratory qualitative study aims to understand uptake and attendance from the perspectives of exercise referral instructors using semi-structured interviews. Six exercise referral instructors from one exercise referral scheme across four exercise referral sites were interviewed. Four themes emerged: (i) the role that instructors perceive they have and approaches instructors take to motivate participants to take-up, attend exercise referral and adhere to their exercise prescription; (ii) instructors’ use of different techniques, which could help elicit behaviour change; (iii) instructors’ perceptions of participants’ views of exercise referral schemes; and (iv) barriers towards providing an exercise referral scheme. Exercise referral instructors play an important, multifaceted role in the uptake, attendance and adherence to exercise referral. On-going education and peer support for instructors may be useful. Instructors’ perspectives help us to further understand how health and leisure services can design successful exercise referral schemes.
Research on Fuzzy Control Automotive Electronic Power Steering Characteristic

The driving stability and comfort-ability are directly influenced by steering system, and it is a critical component in an automobile. Torsion bar torque sensor signal and the vehicle speed signal are used to calculate the assisting torque that on the motor shaft. The rules about how to calculate desired torque signal is very important for driving portability and stability. Influence of motor control strategy on assisting response characteristic. In this paper adaptive fuzzy control rules is proposed for the assisting characteristic and power motor. Base on assistance characteristic and assistance motor fuzzy control is designed. Fuzzy information processing torque signal, vehicle speed signal, with MATLAB simulation contrast experiment, and the result validation the fuzzy controller.
Butting Heads on Matched Cohort Analysis Using SAS ® Software

Matched-pair cohort studies involve pairs of cases where outcomes of interest (e.g., mortality, morbidity, injury, etc.) among persons exposed to risk factors are compared with persons not exposed. Matched cohort studies have been used in traffic-crash research, for example, to compare the injury risk of drivers and passengers from the same crash or vehicle. Matching in cohort studies helps reduce bias and confounding effects that may exist in estimating risk or hazard ratios. Only the data where one or both of the paired cases with the outcome of interest are used, which is useful when little or no information is available regarding pairs in which cases did not have the outcome. For example, this technique could be used to analyze a registry of disease or trauma cases, since no information would be available on the number of cases that are disease or trauma free. Mantel-Haenszel stratification, logistic and conditional Poisson regression, and Cox proportional hazard models are common methods used to analyze data from cohort studies. This paper will show how SAS procedures GENMOD (for conditional Poisson regression) and PHREG (for Cox proportional hazards regression) can be used to analyze matched-pair cohort data in traffic crash research.
Effect of Dietary Sodium Restriction on the Quality of Life of Patients With Heart Failure

Background Dietary salt restriction is recommended by many guidelines for patients with heart failure (HF). Quality of life (QoL) is an important end point of this intervention. However, the literature is still limited regarding the effect of dietary salt restriction on QoL in patients with HF. Aims We performed a systematic review and meta-analysis of randomized controlled trials to evaluate the effect of dietary sodium restriction on QoL in patients with HF. Methods We searched PubMed (MEDLINE), the Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, and Cumulative Index to Nursing and Allied Health from the establishment of each database to December 20, 2020. We included randomized controlled trials with sodium restriction as an intervention. The primary outcome was QoL, and the secondary outcomes were mortality, readmission, and fatigue. We obtained the full text of potentially relevant trials, extracted data from the included trials, assessed their risk of bias, and performed a meta-analysis. Results We included 10 trials (1011 participants with HF) with 7 days to 83 months of follow-up. Dietary sodium restriction did not improve QoL over the long term (>30 days) (P = .61). The pooled effects showed that this intervention might increase mortality risk (P < .00001). It did not reduce the readmission rate within the short term (≤30 days) (P = .78) but increased the readmission rate over the long term (P = .0003). Conclusion Our study did not show that interventions to restrict dietary sodium had a positive effect on patients with HF in terms of QoL, mortality, or readmission.