Miracle-dz/UniFAR-FTUs huggingface dataset:
CORRELATION OF INTRAOCULAR PRESSURE WITH OCULAR AXIAL LENGTH AFTER INTRAVITREAL INJECTION OF BEVACIZUMAB IN DIABETIC MACULAR EDEMA

Objective: To determine the effect of Intravitreal injection of Bevacizumab on IOP in eyes of different axial lengths.Study Design: Cross sectional study.Place and Duration of Study: This study was conducted at AFIO Rawalpindi, from Sep 2013 to Jan 2014.Material and Methods: In this study 55 patients scheduled for intravitreal injection of bevacizumab for the treatment of diabetic macular edema were enrolled. An informed written consent was taken from all the patients. All patients underwent clinical ophthalmic examination including uncorrected distance visual acuity, corrected distance visual acuity, slit lamp bio-microscopy and fundus examination with 90 diopter lens. Axial length was measured before IVB using IOL master. Intra Ocular Pressure (IOP) was measured before and after 1 minute of administration of Intravitreal Bevacizumab (IVB) using Tono-Pen.Result: The mean age of patients was 54.51 ± 7.53 years with minimum age of 43 years and maximum age of 70 years. There were 26 (47.3%) male and 29 (52.7%) female patients. The mean axial length of the examined eyes was 21.12 ± 1.80 with range of 6 mm. Mean IOP before IVB was 13.09 ± 1.62 mmHg. After 1 minute of IVB, mean IOP was 32.8 ± 6.19 mmHg. A good correlation was observed between the axial length and intraocular pressure rise after 1 min i.e. Pearson correlation (r.) = -0.914 (p-value <0.001) with R2 = 0.835. Conclusion: There is significant rise in IOP after intravitreal injection of bevacizumab in patients with short axial length as compared to long axial length.
A Viewpoint on Embodied Synthetic Agency

An artificial (synthetic) intelligence can enjoy no more complex domain of sensory input than that provided by instantiation within an autonomous vehicular device. In order to embody an artificial intelligence (a synthetic agency) within a vehicular device (a host), the system designer must be prepared to integrate an array of mechanical components together with computational hardware, mission-specific behavioral heuristics, and autonomous control algorithms. Systems whose requirements specify adaptive, stimulus generalized, and purposive sensorimotor behavior may be a lesser challenge to design, if a degree of non-deterministic system behavior is allowed. However, the opposite is true for military systems that will require demonstration of not only deterministic concrete and even formal reasoning behavior but also retain positive control over an array of lethal and survival-motivated sensorimotor behaviors. Such “cognate” systems will have an implicit need for mechanisms that map raw sensation onto dissimilar cognitive sub-processing elements. Common to these systems will be the problem that the mechanism(s) they employ to map raw sensation onto cognitive sub-processes will be plagued by inherent representational, scope limited, and frame of reference offset errors. Further, all of these problems will be exacerbated in systems where specifications require evidence of agent learning as a deliverable. Obviously, these are not trivial problems and their solution will require methods derived from a variety of sources. In this essay, the author describes a focused array of principles taken from cybernetics and biogenicpsychology, a controversial view of intelligence, and a Turing algorithm history misplaced. Taken together, the author has found the principles useful in creating models of synthetic agency and host interface technology.
Semantic Similarity Based Data Alignment Using Ontology and Swarm Intelligence Based Annotating Search Results from Web Databases

Deep analysis of the SRRs from Web databases (WDB) plays major important role to find exact searching for each user and improve the web pages by analysis results. The number of web pages returned from the WDB is known search result records (SRRs); it consists of the several numbers of pages. These returned web pages results becomes complex to analysis each data unit since it consists of several number of data unit . To overcome the problem of web analysis in earlier work proposes an annotation methods where the data and text unit nodes are converted in the form of table, but in these work the data and unit nodes are not semantically measured labeled . In order to conquer these problem in this paper propose an ontology based data alignment method to Semantically label each data units in the annotated table for each and every SRRs returned from WDBs. This ontology based data alignment algorithm extract data and text unit nodes features from the SRRs through PSO and then data are aligned based on the semantically labeled named results from ontology. Then perform the swarm intelligence based ABC algorithm to select best search results from annotated table result through the colony of artificia l bees . The colony of the ABC consists of the three major bees such as employed, onlookers and scouts bees. Each and every bee in the ABC selects best annotated search results through the behavior of the ABC for annotated table. Then, for each selected search results annotated it again in different point of the view and combined the dissimilar annotations to anticipate an absolute annotation label intended for it. Our experiments results indicates that the proposed DA-ABC algorithm have high precision and recall result for book application when compare to existing data
Modeling Detailed Cloud Scene from Multi-source Images

Realistic cloud is essential for enhancing the quality of computer graphics applications, such as flight simulation. Data-driven method is an effective way in cloud modeling, but existing methods typically only utilize one data source as input. For example, natural images are usually used to model small-scale cloud with details, and satellite images and WRF data are used to model large scale cloud without details. To construct large-scale cloud scene with details, we propose a novel method to extract relevant cloud information from both satellite and natural images. Experiments show our method can produce more detailed cloud scene comparing with existing methods.
Potential of digital sensors for land cover and tree species classifications - a case study in the framework of the DGPF-project

Summary: The study is intended as a contribution to assessing the value of digital image data for semi-automatic analysis for classifying land cover and tree species and was carried out in the framework of the DGPF-project. Sensor specific strengths of ADS40-2 nd , Quattro DigiCAM, DMC, JAS-150, Ultracam-X, and RMK-Top15 cameras and weakness for classification purposes are presented and shortly discussed. The first approach is based on a maximum likelihood method in combination with a decision tree and produces 13 land cover classes. The second approach is based on logistic regression models and produces eight tree species classes. The classified images were visually assessed and quantitatively analyzed. The accuracy assessment reveals that in both approaches similar classification results are obtained by all sensors with overall Kappa coefficients between 0.6 and 0.9. However, a real sensor comparison was not possible since the image data was acquired at different dates. Thus, some variations in classification results are due to phenological differences and different illumination and atmospheric conditions. It is planned for the future that the classifications of the first approach will be adjusted to the characteristics of each sensor. In the second approach, further work is needed to improve distinguishing non-dominant, small and covered deciduous tree species. Zusammenfassung: Potenzial digitaler Sensoren zur Klassifizierung der Landbedeckung und Baumarten - eine Fallstudie im Rahmen des DGPF-Projektes. Anhand der Bilddaten aus den Kamerasystemen ADS40-2 nd , Quattro DigiCAM, DMC, JAS-150, Ultracam-X, und RMK-Top15 wurden zwei Klassifikationsverfahren (Maximum Likelihood und logistische Regression) getestet. Dabei wurden sensor-spezifische Eigenschaften erlautert, sowie die Starken und Schwachen der einzelnen Systeme aufgezeigt. Die Resultate wurden visuell und quantitativ bewertet. Direkte Sensorvergleiche erwiesen sich dabei als schwierig, da zum Aufnahmezeitpunkt der einzelnen Bilddaten sowohl eine unterschiedliche Vegetationsentwicklung wie auch Unterschiede in den Beleuchtungs- und atmospharischen Verhaltnissen vorherrschten. Quantitative Analysen zeigen, dass sich mit jedem Kamerasysteme sehr ahnlich gute Resultate erzielen liessen. Das erste Verfahren zeigt fur 13 Landnutzungsklassen Kappa Koeffizienten von gut 0.6 bei allen verwendeten Systemen. Allerdings unterscheidet sich die Genauigkeit der einzelnen spezifischen Klassen wie Mais oder Kartoffeln fur die unterschiedlichen Kameras. Hierzu soll in weiteren Analysen das Klassifikationsverfahren an die jeweiligen Kameras angepasst werden. Fur das zweite Verfahren liegt der Kappa Koeffizient fur 8 Baumarten zwischen 0.7 und 0.9. Bei diesem Verfahren soll in zukunftigen Analysen die Genauigkeit der Erkennung von nicht dominanten, kleinen und verdeckten Baumarten erhoht werden.
Analysis of a hybrid PWM based on modified space vector and triangle comparison methods

Classical space vector PWM with equal duration of application of zero state vectors V/sub 0/ and V/sub 7/ was modified. A factor-variable k/sub 0/ (proportional to the time of application of vector V/sub 7/) was introduced. By changing k/sub 0/ from 0 to 1, the duration of application of V/sub 7/ can be changed from 0% to 100% of the combined application time for zero state vectors. Correlation between modified space vector and triangle comparison methods (with added zero sequence) was established. The influence of factor k/sub 0/ on characteristics of the PWM was investigated. An expression for the optimal value of k/sub 0/ which provides minimum ripple in the load current was derived. Salient features of the new algorithm are: extended linearity (up to 1.154), reduced switching losses and ability to change the current spectrum by changing k/sub 0/ every sampling time. The developed algorithm is suitable for microprocessor and analog implementation. Since the new algorithm combines theory of space vector with ease of implementation of a triangle comparison PWM it is named "hybrid" PWM (HPWM).
Contourlet Cryptography: A Better Description for Pattern Recognition

In the application of Computer vision research, Wavelets have enjoyed widespread popularity. In recent perspective some new age transforms like the corex transform, steerab le Pyramid, ridgelets, contourlets and curvelets are theoretically appearing to the better image description for pattern recognition. These new transforms have been applications in the area of compression, denoising, watermarking and digital signature systems. In this work we will compare the performance of wavelets and contourlets for the purpose of pattern recognition cryptography. The results are based on well known database experiments viz USPS database of handwritten numerals and the Essexface database. We chose K-Nearest Neighbor and Probabilistic Neural Network for the purpose of classification. The result indicates that although contourlets surpass wavelets for other image processing tasks like compression and denoising, they are not good as wavelets for the purpose of pattern recognition until or unless cryptography is involved.
Modeling, Stability Analysis, and Control of Distributed Generation in the Context of Microgrids

One of the consequences of competitive electricity markets and international commitments to green energy is the fast development and increase in the amount of distributed generation (DG) in distribution grids. These DGs are resulting in a change in the nature of distribution systems from being “passive”, containing only loads, to “active”, including loads and DGs. This will affect the dynamic behavior of both transmission and distribution systems. There are many technical aspects and challenges of DGs that have to be properly understood and addressed. One of them is the need for adequate static and dynamic models for DG units, particularly under unbalanced conditions, to perform proper studies of distribution systems with DGs (e.g., microgrids). The primary objective of this thesis is the development and implementation of dynamic and static models of various DG technologies for stability analysis. These models allow studying systems with DGs both in the longand short-term; thus, differential and algebraic equations of various DGs are formulated and discussed in order to integrate these models into existing power system analysis software tools. The presented and discussed models are generally based on dynamic models of different DGs for stability studies considering the dynamics of the primary governor, generators, and their interfaces and controls. A new comprehensive investigation is also presented of the effects of system unbalance on the stability of distribution grids with DG units based on synchronous generator (SG) and doubly-fed induction generator (DFIG) at different loading levels. Detailed steadystate and dynamic analyses of the system are performed. Based on voltage and angle stability studies, it is demonstrated that load unbalance can significantly affect the distribution system dynamic performance. Novel, simple, and effective control strategies based on an Unbalanced Voltage Stabilizer (UVS) are also proposed to improve the system control and the stability of unbalanced distribution systems with SGand DFIG-based DGs.
A multiple parameter test case prioritization model

Abstract Test case prioritization involves scheduling test cases in an order that increases their effectiveness in meeting some performance goals. One of the most important performance goals is the rate of fault detection. Test cases should be run in an order that increase the chances of fault detection and also that catch the most critical faults at the earliest. In this paper, we propose a model of test case prioritization from Software Requirement Specification. The model takes the combined effect of three different parameters of software functionality i.e., Usage Frequency of function, Criticality of the fault and Complexity of the function. The model being Fuzzy does not require accurate calculation of parameters of software, which is also not realistic at an early stage of software development.
Improving Lightweight Data Sharing Scheme for Compatibility with Advanced Encryption Standard

—Cloud computing is the availability of computer system resources on demand, in particular data storage and computing power, without direct active user management. But the main disadvantage with cloud-based storage is the security of the stored documents. Because cloud service providers have access to cloud content, they would benefit greatly from using user data for various purposes such as advertising. That would invade the user’s privacy. Mobile devices are now able to store and retrieve data from anywhere with the popularity of cloud computing. This would have a major security issue as there are insufficient resources for mobile devices to run complex encryption algorithms. Lightweight data sharing scheme(LDSS) has therefore been introduced and the algorithm uses CP-ABE technology to enable encryption based on attributes. LDSS-CP-ABE algorithm based on Attribute-Based Encryption(ABE) method to provide effective ciphertext access control. A normal ABE operation takes 27 times longer to run on a mobile platform and this overhead was reduced by LDSS-CP-ABE. But this is not compatible with the popular AES standard for encryption. We suggest a method for integrating AES and LDSS-CP-ABE algorithms in this paper.We likewise propose another component for the working of LDSS without requiring to utilize encryption and decoding servers independently. This would essentially diminish the expense of actualizing the calculation and would have no impact on the execution.
Tactile sensitivity in ultrasonic haptics: Do different parts of hand and different rendering methods have an impact on perceptual threshold?

Abstract Background Ultrasonic tactile representation utilizes focused ultrasound to create tactile sensations on the bare skin of a user’s hand that is not in contact with a device. This study is a preliminary investigation on whether different ultrasonic haptic rendering methods have an impact on the perceptual threshold. Methods This study conducted experiments with the adaptive step method to obtain participants’ perceptual thresholds. We examine (1) whether different parts on the palm of the hand have different perceptual thresholds; (2) whether the perceptual threshold is different when the ultrasonic focus point is stationary and when it moves in different trajectories; (3) whether different moving speeds of the ultrasonic focus point have an influence on the perceptual threshold; and (4) whether the addition of a DC offset to the modulating wave has an impact on the perceptual threshold. Results The results show that the center of the palm is more sensitive to ultrasonic haptics than the fingertip; compared with a fast-moving focus point, the palm is more sensitive to a stationary and slow-moving focus point. When the modulating wave has a DC offset, the palm is sensitive to a much smaller modulation amplitude. Conclusion For the future ultrasonic tactile representation systems, dynamic adjustment of intensity is required to compensate the difference in perceptual thresholds under different rendering methods to achieve more realistic ultrasonic haptics.
An Imbalanced Spam Mail Filtering Method

The high false alarm rate appears during the traditional spam recognition method processing the large-scale unbalanced data. A method which transforms the unbalanced issue into the balanced issue is proposed, when the K-means clustering algorithm is improved based on the support vector machine classification model, to obtain the balanced training set. Firstly, the improved K-means clustering algorithm clusters spam and extracts the typical spam，then the training set consists of the typical spam and legitimate messages, and finally the goal of the filtration of spam is realized by trained SVM classification model. Comparing the K-SVM filtration method to standard SVM method through the experiment, the result indicates that the K-SVM filtration method in large-scale unbalance data set can obtain high classified efficiency and the generalization performance.
Vehicle-to-grid (V2G) Reactive Power Operation Analysis of the EV/PHEV Bidirectional Batt ery Charger

More battery powered electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) will be introduced to the market in 2013 and beyond. Since these vehicles have large batteries that need to be charged from an external power source or directly from the grid, their charging circuits and grid interconnection issues are garnering more attention. It is possible to incorporate more than one operation mode in a charger by allowing the power to flow bidirectionally. Usually, the bidirectional power transfer stands for two-way transfer of active power between the charger and the grid. The general term of sending active power from the vehicle to the grid is called vehicle to grid (V2G). While plug-in electric vehicles (PEVs) potentially have the capability to fulfill the energy storage needs of the electric grid, the degradation on the battery during this operation makes it less preferable by the auto manufacturers and consumers. On the other hand, the on-board chargers can also supply energy storage system applications such as reactive power compensation, voltage regulation, and power factor correction without the need of engaging the battery with the grid and thereby preserving its lifetime. This study shows the effect of reactive power operation on the design and operation of single-phase on-board chargers that are suitable for reactive power support. It further introduces a classification of single-phase ac-dc converters that can be used in on-board PEV chargers based on their power transfer capabilities in addition to the currently available surveys.
An evolutionary approach for VLSI standard cell design

Standard cell design is a challenging task faced by VLSI chip designers. Traditional methods of standard cell design automation rely on a schematic representation supplied by a design engineer. We have demonstrated the possibility of applying a genetic algorithm (GADO) to design a cell given only a behavioral description (truth table). A working inverter is designed as a proof of concept.
Mechanics of Terrestrial Locomotion: With a Focus on Non-pedal Motion Systems

This book covers the specific aspects of mechanics and control theory that are applied in terrestrial locomotion systems. In addition to the theoretical basics exercises are provided. The book also comes packaged with: - Video files of prototypes of wheeled and worm-like locomotion systems; - E-learning Software on the mechanical background; - MAPLE programs for the dynamic simulation of locomotion systems.
PERANAN APARATUR DESA DALAM MENINGKATKAN PARTISIPASI MASYARAKAT MENGIKUTI WAJIB BELAJAR 12TAHUN

Demografi pendidikan di desa Rawa sangat minim dalam penuntasan belajar 12 tahun, Wajib belajar yang dicanangkan oleh pemerintah sebagian besar belum tercapai, disebabkan oleh beberapa faktor antara lain, keadaan ekonomi, jarak tempuh ke tempat pendidikan , lingkungan masyarakat, pesimisme orang tua terhadap pendidikan serta rendahnya motivasi belajar anak. Tujuan Penelitian ini adalah untuk mengetahui peranan aparatur desa dalam meningkatkan partisipasi masyarakat mengikuti wajib belajar 12 tahun. Metode yang digunakan adalah deskriptif kualitatif. Subjek dalam penelitian ini adalah Aparatur Desa, dengan mengambil informan Kepala Desa, Kasi Pemerintahan Desa, Kepala Dusun, Masyarakat, Guru dan Siswa. Analisis data dalam penelitian ini mengunakan metode analisis interaktif. Adapun prosedurnya meliputi pengumpulan data, reduksi data, penyajian data, dan verifikasi data selanjutnya menjadikan kesimpulan. Hasil penelitian berdasarkan hasil analisis data dan pembahasan yang diuraikan, (1) Bahwa peranan aparatur desa dalam meningkatkan partisipasi masyarakat mengikuti wajib belajar 12 tahun kurang berperan karena sebagai kepala desa beliau hanya melakukan sosialisasi ataupun penyuluhan hanya di 2 (dua) dusun saja, sedangkan 3 dusun lagi sangat minim akan informasi. (2) Bahwa partisipasi masyarakat Desa Rawa mengikuti wajib belajar 12 tahun kurang karena hanya di 2 Dusun saja yang sudah cukup baik partisipasinya sedangkan di 3 Dusun kurang atau minim partisipasinya. (3) Faktor-faktor yang menjadi kendala atau hambatan masyarakat tidak mengikuti wajib belajar 12 tahun yaitu: Ekonomi, lingkungan, jarak, karena pesimisme masyarakat terhadap anak sekolah yang dianggap tidak mampu memperoleh pekerjaan yang layak setelah menyelesaikan studinya, rendahnya jenjang pendidikan yang dimiliki masyarakat menjadikannya tidak terbuka. Saran Desa Rawa terletak di daerah pedaratan tinggi dengan kontur yang tidak terlalu curam sehingga wilayahnya menanjak dan menurun seperti wilayah di daerah perbukitan. Masyarakat disana umumnya bermata pencaharian sebagai Petani. Peran aparatur desa dalam meningkatkan partisipasi masyarakat kurang karena kepala desa hanya melakukan sosialisasi di 2 dusun saja sedangkan 3 dusun lagi kurang atau minim informasi. Peran aparatur desa khususnya kepala desa, dan kepala dusun dalam pelaksanaannya melakukan kerjasama dengan dinas pendidikan terkait dan tokohtokoh pendidikan, seperti sekolah-sekolah dan masyarakat yang berprofesi sebagai guru atau tenaga pendidik. Kata Kunci : Aparatur Desa, Partisipasi Masyarakat, Wajib Belajar 12 Tahun