Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Optimization and Assessment of Floating Solar PV with Wind Turbine Systems at KEPZ

Renewable energy holds enormous potential in Bangladesh, but significant obstacles must be overcome to fully harness its benefits. With natural gas being the primary source of power generation in the country, there is a growing need to explore alternative sources of energy to reduce emissions and relieve the pressure on limited fuel supplies. Wind turbines (WT) and solar photovoltaic (PV) systems are currently being deployed to harness renewable energy, and Bangladesh's unique geographical features, including being a riverine country with a modest land area, make it an ideal candidate for floating PV and WT installations. However, the intermittency of renewable generation and high upfront costs pose significant challenges to the technical and economic feasibility of microgrid operation. The use of Energy Management Systems (EMS) and Grey Wolf Optimization (GWO) can help optimize the use of renewable resources and minimize capital costs, respectively. In this research, a methodology is proposed to assess the economic feasibility of floating PV and WT in the Korean Export Processing Zone (KEPZ), a critical hub of the country's economic activity, while minimizing renewable energy costs using the GWO technique. Mathematical models are used to design the hybrid renewable system, and load-demand data is collected from KEPZ. Based on hourly resource data, annual hourly floating PV and WT energy generation is estimated, and the electricity cost (LCEO) is evaluated, yielding a cost of 0.099$/kWh for the system, taking into account project lifetime, interest rate, and inflation rate.
HomeSGN: A Smarter Home with Novel Rule Mining Enabled by a Scorer-Generator GAN

Most contemporary research in advanced smart homes has been primarily focused on understanding the environment and identifying activities. However, it can never translate these insights into actionable rules that could improve residents’ quality of life, much less optimize the entire home environment. Addressing this gap, our paper introduces HomeSGN, an end-to-end trainable Scorer-Generator system founded on the Generative Adversarial Network (GAN) architecture. Specifically tailored for smart home applications, HomeSGN extracts, assesses, and proffers beneficial rules from residents’ everyday activities, thereby improving living conditions and optimizing the home environment with adaptable targets. Complemented by pioneering data augmentation and rectification strategies, the system assures model stability, avoids mode collapse, and maintains data integrity throughout GAN training. Integrating HomeSGN into an existing smart home infrastructure establishes a seamless sensor-to-rule pipeline. The effectiveness of HomeSGN is underscored by significant benefits, notably an enhancement of life quality by over 50% in single-user homes and 30% in multi-user scenarios, thus truly embodying the promise of “smart” in smart homes.
LODES: Local Density Meets Spectral Outlier Detection

_e problem of outlier detection has been widely studied in existing literature because of its numerous applications in fraud detection,medical diagnostics, fault detection, and intrusion detection. A large category of outlier analysis algorithms have been proposed, such as proximity-based methods and local density-basedmethods. _esemethods are effective in ûnding outliers distributed along linear manifolds. Spectral methods, however, are particularly well suited to ûnding outliers when the data is distributed along manifolds of arbitrary shape. In practice, the underlying manifolds may have varying density, as a result of which a direct use of spectral methods may not be eòective. In this paper, we show how to combine spectral techniques with local density-based methods in order to discover interesting outliers. We present experimental results demonstrating the eòectiveness of our approach with respect to well-known competing methods.
Brief communication: Supraglacial debris-cover changes
in the Caucasus Mountains

Abstract. Debris cover on glaciers can significantly alter melt, and hence, glacier mass balance and runoff. Debris coverage typically increases with shrinking glaciers. Here, we present data on debris cover and its changes for 559 glaciers located in different regions of the Greater Caucasus mountains based on 1986, 2000 and 2014 Landsat and SPOT images. Over this time period, the total glacier area decreased from 691.5 km2 to 590.0 km2 (0.52 % yr−1). Thereby, the debris covered area increased from ~ 11 to ~ 24 % on the northern, and from ~ 4 to 10 % on the southern macro-slope between 1986 and 2014. Overall, we found 18 % debris cover for the year 2014. With the glacier shrinkage, debris-covered area and the number of debris-covered glaciers increased as a function of elevation, slope, aspect, glacier morphological type, Little Ice Age moraines, and lithology.
Failure Analysis of IoT-based Smart Agriculture System: Towards Sustainable Food Security

Internet of Things (IoT)-based smart agriculture systems are increasingly being used to improve agricultural yield. IoT devices used for agricultural monitoring are often deployed in outdoor environments in remote areas. Due to the exposure to harsh environments and the nature of deployment, sensors and other devices are susceptible to an increased rate of failure, which can take a system to unsafe and dangerous states. Failure of a smart agriculture system can cause significant harm to nature and people and reduce agricultural production. To address the concerns associated with the failure of the system, it is necessary to understand how the failures of the components of a system can contribute to causing the overall system failure. This paper adopts Fault Tree Analysis, a widely used framework for failure behaviour analysis in other safety-critical domains, to demonstrate the qualitative failure analysis of smart irrigation systems based on the components' failure.
Importin α7 Is Essential for Zygotic Genome Activation and Early Mouse Development

Importin α is involved in the nuclear import of proteins. It also contributes to spindle assembly and nuclear membrane formation, however, the underlying mechanisms are poorly understood. Here, we studied the function of importin α7 by gene targeting in mice and show that it is essential for early embryonic development. Embryos lacking importin α7 display a reduced ability for the first cleavage and arrest completely at the two-cell stage. We show that the zygotic genome activation is severely disturbed in these embryos. Our findings indicate that importin α7 is a new member of the small group of maternal effect genes.
Insecticidal efficacy of Chrysanthemum cinerariaefolium Seed Oil Against Cowpea Beetle and Its Impact on the Physicochemical and Technological Characteristics of Cowpea during Storage

Essential oil from Chrysanthemum cinerariaefolium seeds was extracted using a soxhlet extractor for 48 hours. The oil extract's insecticidal activity against adult cowpea beetles (Callosobruchus maculatus) was investigated at concentrations of 0.01, 0.03, 0.05, 0.1, and 0.18%. Data showed that seed extract caused significant insect mortality. The mortality percentage reaches 100% after three days of exposure at a concentration of 0.18% of the extract. Data was carried out on the effect of oil on some biological aspects of C. maculatus (total number of eggs, egg hatchability, adult emergence, and reduction percentage). The LC 95 (0.4%) of Chrysanthemum oil was assessed for physicochemical and technological characteristics during a storage period of 12 weeks. The treated cowpea seeds showed an unchanged chemical composition at zero time. During storage periods, the tested treatment reduces the rate of decreasing length, width, lightness, and redness. The 1000 - weight seed and yellowness value were higher in treated seeds than in untreated seeds. A decrease in the cooking time and total soluble solids of treated cowpea seeds during storage. While the water uptake ratio, hydration and swelling capacity, the moisture, protein content and in vitro protein digestibility of treated cowpea seeds were higher than those of the untreated at the end of storage, the treated cowpea seed samples were acceptable in all tests of sensory acceptability. This study recommended using Chrysanthemum seed oil (0.4%) for management of the C. maculatus population while maintaining the nutritional and technological quality of cowpea seeds during storage and avoiding risks from chemical insecticides.
Rate-Distortion Performance of Sequential Massive Random Access to Gaussian Sources with Memory

In Sequential Massive Random Access (SMRA) [1, 2], a set of correlated sources is jointly encoded and stored on a server, and clients want to access to only a subset of the sources. Since the number of simultaneous clients can be huge, the server is only authorized to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of a request. In this paper, we investigate the SMRA performance of lossy source coding of Gaussian sources with memory. In practical applications such as Free Viewpoint Television, this model permits to take into account not only inter but also intra correlation between sources. For this model, we provide the storage and transmission rates that are achievable for SMRA under some distortion constraint, and we consider two particular examples of Gaussian sources with memory.
A low complexity receiver for space-time coded CDMA systems

A novel receiver for space-time coded systems based on the reduced rank multistage Wiener filter (MWF) is presented. It is shown that this receiver has a complexity that is only a linear function of the processing gain (N), the number of transmit antennas (Lt), and the rank (D) of the MWF. The complexity of the equivalent MMSE solution is a function of (N Lt)3. It is also demonstrated by numerical simulation that this receiver meets MMSE performance at a significantly lower rank. The MMSE implementation is derived and performance is evaluated for highly loaded synchronous CDMA systems in flat fading.
Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico

PURPOSE Multiple intrapersonal and structural barriers, including geography, may prevent women from engaging in cervical cancer preventive care such as screening, diagnostic colposcopy, and excisional precancer treatment procedures. Geographic accessibility, stratified by rural and nonrural areas, to necessary services across the cervical cancer continuum of preventive care is largely unknown. METHODS Health care facility data for New Mexico (2010-2012) was provided by the New Mexico Human Papillomavirus Pap Registry (NMHPVPR), the first population-based statewide cervical cancer screening registry in the United States. Travel distance and time between the population-weighted census tract centroid to the nearest facility providing screening, diagnostic, and excisional treatment services were examined using proximity analysis by rural and nonrural census tracts. Mann-Whitney test (P < .05) was used to determine if differences were significant and Cohen's r to measure effect. FINDINGS Across all cervical cancer preventive health care services and years, women who resided in rural areas had a significantly greater geographic accessibility burden when compared to nonrural areas (4.4 km vs 2.5 km and 4.9 minutes vs 3.0 minutes for screening; 9.9 km vs 4.2 km and 10.4 minutes vs 4.9 minutes for colposcopy; and 14.8 km vs 6.6 km and 14.4 minutes vs 7.4 minutes for precancer treatment services, all P < .001). CONCLUSION Improvements in cervical cancer prevention should address the potential benefits of providing the full spectrum of screening, diagnostic and precancer treatment services within individual facilities. Accessibility, assessments distinguishing rural and nonrural areas are essential when monitoring and recommending changes to service infrastructures (eg, mobile versus brick and mortar).
The effect of vertical expandable prosthetic titanium rib on growth in congenital scoliosis

Aims: In the treatment of thoracic insufficiency syndrome, the main aim is to maintain spinal and thoracic growth in order to continue respiratory functions. Vertical expandable prosthetic titanium rib (VEPTR) device application is a method of choice especially in the congenital cases with a thoracic deformity. In our study, we evaluated the effect of VEPTR on growth in congenital scoliosis. Materials and Methods: Four female patients in whom VEPTR was applied were retrospectively evaluated. Anteroposterior (AP) and lateral Cobb angles that were measured preoperatively and during the last control, space available for lung (SAL), T1-S1 and T1-T12 distances, coronal and sagittal balances were compared. Results: Four female patients in whom VEPTR was applied were retrospectively evaluated. AP and lateral Cobb angles that were measured preoperatively and during the last control, SAL, T1-S1, and T1-T12 distances, coronal and sagittal balances were compared. Conclusions: VEPTR may provide a good correction, and we observed a growth in the spine height and SAL following the treatment of congenital deformities. Long-term, multicenter, prospective studies that compare the spinal height, respiratory functions, the severity of the deformity, and the spinal balance are required in order to evaluate the efficacy of VEPTR.
RC Interconnect Model Order Reduction with Truncation Balanced Reduction

Interconnect becomes one of the major factors of today's VLSI circuit design. Its modeling and simulation are becoming more challenging and very difficult. This paper describes the truncation balanced reduction (TBR) algorithms in the model reduction of RC interconnect. Simulation is executed to RC interconnect and may be improve VLSI interconnect system modeling and design technology.
Estimates of Wildfire Emissions in Boreal Forests of China

Wildfire emissions in the boreal forests yield an important contribution to the chemical budget of the troposphere. To assess the contribution of wildfire to the emissions of atmospheric trace species in the Great Xing’an Mountains (GXM), which is also the most severe fire-prone boreal forest region in China, we estimated various wildfire activities by combining explicit spatio-temporal remote sensing data with fire-induced emission models. We observed 9998 fire scars with 46,096 km2 in the GXM between the years 1986 and 2010. The years 1987 and 2003 contributed 33.2% and 22.9%, respectively, in burned area during the 25 years. Fire activity is the strongest in May. Most large fires occurred in the north region of the GXM between 50° N and 54° N latitude due to much drier weather and higher fire danger in the northern region than in the southern region of the study domain. Evergreen and deciduous needleleaf forest and deciduous broadleaf forest are the main sources of emissions, accounting for 84%, 81%, 84%, 87%, 89%, 86%, 85% and 74% of the total annual CO2, CH4, CO, PM10, PM2.5, SO2, BC and NOx emissions, respectively. Wildfire emissions from shrub, grassland and cropland only account for a small fraction of the total emissions level (approximately 4%–11%). Comparisons of our results with other published estimates of wildfire emissions show reasonable agreement.
Optimal Information Decoding from Neuronal Populations with Specific Stimulus Selectivity

A typical neuron in visual cortex receives most inputs from other cortical neurons with a roughly similar stimulus preference. Does this arrangement of inputs allow efficient readout of sensory information by the target cortical neuron? We address this issue by using simple modelling of neuronal population activity and information theoretic tools. We find that efficient synaptic information transmission requires that the tuning curve of the afferent neurons is approximately as wide as the spread of stimulus preferences of the afferent neurons reaching the target neuron. By meta analysis of neurophysiological data we found that this is the case for cortico-cortical inputs to neurons in visual cortex. We suggest that the organization of V1 cortico-cortical synaptic inputs allows optimal information transmission.
Torsion Point Cryptography: Enhancing Data Security with Elliptic Curves

Torsion Point Cryptography is an innovative encryption technique that employs the mathematical properties of elliptic curves to ensure maximum security. This research paper delves into the technical intricacies of this approach, elucidating how it operates and why it is so effective. The authors delve into various types of torsion points that can be employed in this cryptography method, including rational and non-rational points, and discuss the benefits and constraints associated with each. They also conduct a thorough analysis of the security implications of torsion point cryptography, comparing it to other commonly used cryptosystems and highlighting its potential vulnerabilities. In conclusion, this paper offers an exhaustive introduction to torsion point cryptography and its real-world applications for secure communication.
Wall following using angle information measured by a single ultrasonic transducer

Conventional wall following with an ultrasonic sensor uses only range data to the nearest reflecting point. However, the bearing angle information to the wall is more useful for a wall following motion. In this paper, we propose a simple wall following algorithm, where the robot moves perpendicular to the direction to the nearest reflecting point. Also, in conventional ultrasonic pulse-echo sensing, an accurate target bearing measurement is often regarded as difficult due to the wide directivity of ultrasonic transducers. However, by assuming that the ultrasonic echo returns from a single direction, the bearing angle can be measured. A new sensing method is also proposed to determine accurately the bearing angle to the reflecting point by a single ultrasonic transducer. This paper also presents experimental results from mobile robot wall following experiments using only bearing information measured by a single ultrasonic transducer. These experiments illustrate the effectiveness of proposed method.
DNA Sequencing by Hybridization Using Semi-Degenerate Bases

One way to enhance the performance of hybridization microarrrays for DNA de novo sequencing is the use of probing patterns with gaps of unsampled positions. Ideally, such gaps could be realized by the inclusion into microarray oligos (probes) of wild-card compounds, referred to as universal bases (which bind nonspecifically to natural bases). The suggested alternative is to deploy in the gap positions degenerate bases, i.e., uniform mixtures of the four natural bases, with ensuing deterioration of the hybridization signal. In this paper, we show that such signal loss is a minor shortcoming, compared with the fact that degenerate bases cannot be treated as universal. Indeed, the substantial spread of hybridization energies at any microarray feature is such that on overwhelming number of mismatches bind more strongly than legal matches. We observed, however, that much narrower energy spreads are exhibited by pairs of bases in the same strength class (A-T and C-G). We call semi-degenerate a gap position realized with bases in the same energy class and show that well-known sequence reconstruction algorithms can be modified to achieve substantial improvements in sequencing effectiveness. For example, with a 4(9)-feature microarray and an acceptable weakening of the hybridization signal, one may achieve lengths of about 4,000 bases (compared with < 250 of the standard uniform method). Our approach also incorporates the use of a spectrum expressed in terms of observed feature melting temperatures (analog spectrum), rather than binary decisions made directly at the biochemical level (digital spectrum). While universal bases represent the ultimate goal of sequencing by hybridization, semidegenerate natural bases are the most effective known substitute.
Feature Point Detection for Real Time Applications

This paper presents a new feature point detector that is accurate, efficient and fast. A detailed qualitative evaluation of the proposed feature point detector for grayscale images is also done. Experi- ments have proved that this feature point detector is robust to affine transformations, noise and perspec- tive deformations. More over the proposed detector requires only 22 additions per pixel to evaluate the interest point and its strength, making it one of the fastest detectors. The accuracy and speed of this al- gorithm makes it a strong contender for ASIC and hardware implementations and applications requiring real time feature point abstraction.
Modeling and Compensation of the Internal Friction Torque of a Travelling Wave Ultrasonic Motor

This paper deals with the control and experimentation of a one-degree-of-freedom haptic stick, actuated by a travelling wave ultrasonic motor. This type of actuator has many interesting properties such as low-speed operation capabilities and a high torque-to-weight ratio, making it appropriate for haptic applications. However, the motor used in this application displays nonlinear behavior due to the necessary contact between its rotor and stator. Moreover, due to its energy conversion process, the torque applied to the end-effector is not a straightforward function of the supply current or voltage. This is why a force-feedback control strategy is presented, which includes an online parameter estimator. Experimental runs are then presented to examine the fidelity of the interface.
THREE-DIMENSIONAL GENUS TOPOLOGY OF LUMINOUS RED GALAXIES

We measure the three-dimensional genus topology of large-scale structure using luminous red galaxies (LRGs) in the Sloan Digital Sky Survey and find it consistent with the Gaussian random phase initial conditions expected from the simplest scenarios of inflation. This studies three-dimensional topology on the largest scales ever obtained. The topology is spongelike. We measure topology in two volume-limited samples: a dense shallow sample studied with smoothing length of 21 h−1 Mpc, and a sparse deep sample studied with a smoothing length of 34 h−1 Mpc. The amplitude of the genus curve is measured with 4% uncertainty. Small distortions in the genus curve expected from nonlinear biasing and gravitational effects are well explained (to about 1σ accuracy) by N-body simulations using a subhalo-finding technique to locate LRGs. This suggests that the formation of LRGs is a clean problem that can be modeled well without any free-fitting parameters. This bodes well for using LRGs to measure the characteristic scales such as the baryon oscillation scale in future deep redshift surveys.