Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Load Balancing Schemes in RPL based Internet of Things

Internet of Things technology is a collection of sensors and actuators which gathers data from physical environment that can be stored and processed to generate actuating information. Physical environment data such as temperature, pressure, humidity, pollution and any valuable parameters related to human body, machine, etc. have great value for automation, fault detection and timely remedy. Thus, IoT networks have given rise to Smart Cities, Smart Health, Smart Transport Logistics, Smart Production and Supply chain management, Smart Home and many more. For IoT deployments, ROLL-WG has standardized Routing Protocol for Low Power and Lossy Networks (RPL) for urban environment (RFC 5548), home automation (RFC 5826), industrial control (RFC 5673) and building automation (RFC 5867). RPL is a destination vector protocol for low power devices which is designed to address the needs of constrained IoT environment. In RPL, nodes organize themselves by forming a Destination Oriented Directed Acyclic Graph (DODAG) rooted towards the sink. RPL uses Objective Functions (ETX & Hop Count) to optimize path selection. Many newObjective Functions for IoT applications are suggested by researchers for path optimization. In most cases, RPL is efficient in providing fast network convergence. However, path optimization and network performance are affected by Load Balancing problem. In this article, we survey existing load balancing schemes in RPL based Internet of Things. We also list out load balancing metrics and challenges in RPL with reference to load imbalance. Keywords— Internet of Things, RPL, Load Balancing schemes, Load Balancing Metrics
RELATIONSHIP AMONG REWARD SYSTEMS , KNOWLEDGE SHARING AND INNOVATION PERFORMANCE

This research attempts to review various researches in term of relationships among reward systems, knowledge sharing and the innovation performance. In this regard, two types of reward are identified, and they are intrinsic reward and extrinsic reward. Extant research showed that reward can affecting innovation performance, so this study proposes a new framework based on mediating role of knowledge sharing. The extrinsic and intrinsic rewards found that they are positively related to the overall innovation performance. This article presents a survey and synthesis of literature on the effects of extrinsic and intrinsic reward on innovation performance and knowledge sharing. The motivational contexts of extrinsic and intrinsic rewards are examined with the purpose of helping the recognize and avoid the potentially harmful effects of poorly designed reward systems. It further found that rewards are positively related to each form of innovation, i.e., product innovation. Research between intrinsic and extrinsic motivation of employees and the expectation of a performance-based reward claims that this study has a better research design. However, it has been proven, with help of questionnaire surveys, that many enterprises still do not measure innovation performance despite the importance of innovation as an engine of growth. Only a few organizations appear to have an effective system for measuring their overall innovation performance.
A General Multi-Sensor Image Analysis System Through Pyramidal Segmentation

A state of the art, fully functional, multi-scale and multi-channel segmentation tool has been developed. It is based on the recently developed computational theory of the 2-normal sepientations. A fast multi-scale pyramidal algorithm has been designed and applied to the theoretical variational segmentation model of Mumford-Shah. This algorithm has a multi-channel capability, as well as a much more general class of solutions. Namely, a piecewise polynomial segmentation is natural to the pyramidal multi-channel framework. The piecewise affine segmentation has been implemented and tested. Application specific channels include: gray scale information, two-dimensional wavelet channels for texture discrimination, and multi-scale singular feature channels. The accuracy of the pyramidal segmentation algorithm has been experimentally compared to the accuracy of two other modern segmentation algorithms. The performance of the pyramidal algorithm has shown an average four-fold reduction in error measurements. Computational experiments with reconnaissance photography, multi-sensor satellite imagery, medical CT and MRI multi-band data have shown a great practical potential of this novel technique. Preliminary experimentation in clutter removal via multi-channel segmentation points to a totally na : class of featurepreserving decluttering algorithms.
A SYSTEMATIC LITERATURE REVIEW ON METHODS FOR SOFTWARE EFFORT ESTIMATION

There have been many researchers who proposed research in an effort to develop the field of improving accuracy in the Software Effort Estimation (SEE). Collected results from a series of studies selected in the Software Effort Estimation, which was published in the period 2000-2017, using systematic mapping and review procedures. The purpose of this review is to provide a classification of study areas of SEE related to publication channels, research approaches, types of contributions, techniques used in combination. To analyze: 1) The precise estimation of SEE techniques; 2) Accuracy of the SEE model estimate compared with other models; 3) A favorable outcome context for the use of the SEE model; and 4) The impact of other techniques into the SEE model by combining models and implementation for models and tools. We have identified 74 major studies that are relevant to the purpose of this study. After investigating, we found that eight types of techniques were used in the Software effort estimation model. that techniques used for SEE usually produce acceptable estimation accuracy, and the facts are more accurate.
Study on Hemigraphis hirta as an Alternative to Antibiotics against Bacteria causing Urinary Tract Infection

a Department of Applied Chemistry and Chemical Engineering, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Bangladesh b Department of Biotechnology and Genetic Engineering, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Bangladesh c Department of Pharmacy, Pusan National University, Busan, Republic of Korea. d Department of Chemistry, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Bangladesh
THE IMPACT OF LECTURE CAPTURE ON STUDENT PERFORMANCE

This paper investigates whether watching online recordings of live lecturers improves student performance on a large first year introductory economics module taught in a Business School. Our results show that performance on other modules and previous experience of economics are the key determinants of performance on this module. However, we also show that watching the lecture recordings may go some way to counteracting a student’s lack of previous experience in the subject.
A perceptual bias for man-made objects in humans

Ambiguous images are widely recognized as a valuable tool for probing human perception. Perceptual biases that arise when people make judgements about ambiguous images reveal their expectations about the environment. While perceptual biases in early visual processing have been well established, their existence in higher-level vision has been explored only for faces, which may be processed differently from other objects. Here we developed a new, highly versatile method of creating ambiguous hybrid images comprising two component objects belonging to distinct categories. We used these hybrids to measure perceptual biases in object classification and found that images of man-made (manufactured) objects dominated those of naturally occurring (non-man-made) ones in hybrids. This dominance generalized to a broad range of object categories, persisted when the horizontal and vertical elements that dominate man-made objects were removed and increased with the real-world size of the manufactured object. Our findings show for the first time that people have perceptual biases to see man-made objects and suggest that extended exposure to manufactured environments in our urban-living participants has changed the way that they see the world.
UTILIZATION OF VEGETABLE WASTE FOR THE CULTIVATION OF P . OSTREATUS AND ITS INFLUENCE ON PHYTOCHEMICALS

Pleurotus ostreatus, Oyster mushroom is one of the common edible mushroom and is the second largest to be cultivated. It belongs to the Class Basidiomycetes and Family Agaricaceae. It grows naturally in temperate and tropical forests on dead and decaying wooden logs and as well as on decaying organic matter. These mushrooms have been used for thousands of years as a culinary and medicinal ingredient. It is one of the most suitable fungal organism for producing protein rich food from various agro waste without composting. The present study proves the enrichment of nutrition in mushroom samples with utilisation of vegetable waste as substrate. The combination of vegetable waste and paddy straw gave better yield in comparison to paddy straw alone. The parameters tested were proximate analysis, qualitative estimation of phytochemicals followed by quantification of phenols and determination of minerals. The fruiting bodies cultivated on vegetable waste in combination of paddy straw accumulated higher concentration of total proteins (20.98mg/g), total carbohydrates (56.57mg/g) and total phenols (344μg /g) than the fruiting bodies cultivated on paddy straw alone which had high moisture content. Crude fat had no significant difference in both the mushroom samples. The present study revealed that the combination of vegetable waste with paddy straw was a better substrate in comparison to paddy straw alone. Also this combination is a promising substrate for cultivating oyster mushroom.
Binaural Direction-of-Arrival Estimation in Reverberant Environments Using the Direct-path Dominance test

Abstract— Speaker localization in reverberant environments is currently an important challenge in audio signal processing, and several methods have recently been proposed to address it. One such family of methods is based on the direct-path dominance (DPD) test that was developed specifically for spherical arrays and recently extended to arbitrary arrays. In this paper, an extension of the DPD test for a binaural array is examined. This extension uses a focusing technique to remove the frequency dependence of the steering matrix within frequency bands. This facilitates frequency smoothing, which is necessary for decorrelating coherent reflections. Unlike other focusing approaches, the proposed focusing approach does not rely on the initial estimation of source directions, facilitating its application in reverberant environments. However, in the binaural case, there is no guarantee of focusing performance. This paper presents an analysis of this focusing process for the binaural case and shows that good focusing performance can be obtained in the binaural case. A simulation study examines the effect of the focusing and smoothing and demonstrates the proposed method’s capabilities in overcoming adverse reverberation conditions.
The Story of Orthopaedics

Introduction PART ONE: ORTHOPAEDICS Adult Hip Osteoarthitis, Arthroplasty, Fractures Childs Hip Perthes, Developmental Dislocation, Slipped Epephysis Foot Hand Spinal Deformity Spinal Pain Cervical Spine Infection Tuberculosis, Osteomyelitis, Septic Arthritis Neuro-Muscular Disease Cerebral Palsy, Polio, Spina Bifida, Muscular Dystrophy Arthritis Gout, Rheumatoid Arthritis, Ankylosing Spondylitis Tumors General Bone Disease Rickets, Osteoporosis, Pagets Disease Amputations and Prostheses Orthopaedic Treatment Methods PART TWO: FRACTURES Injury General Features Lower Limb Fractures Upper Limb Fractures Spine Fractures Fracture Treatment PART THREE: SPORTS MEDICINE Sports and Medicine Knee Shoulder PART FOUR: FINALE Hospitals & the Organization of Care Medical Records and Outcome Studies, Third World, Prevention Conclusions References
DIGITAL ANTHROPOLOGY : THEORETICAL PERSPECTIVES REGARDING ELECTRONIC TRIBES

In this article I approach several theoretical perspectives regarding electronic tribes. Throughout this article, I reveal several arguments about how the flexibility and speed of electronic media has determined new ways of defining human interaction. I also emphasize some of the cultural implications entailed by the emergence of electronic tribes. In the end, I discuss about the relation between e-tribes, ‘cyberscapes’ and cyberspace. I argue that, just as the real cultures include complex systems of significance that are developed in order to address the various issues of everyday life, in cyberspace, the members of e-tribes have developed ‘virtual cultures’. I conclude by comparing cyberspace with Plato’s World of Ideas.
Misha Mittal , Abhilasha Recent Work on Clause Identification Indian and English Languages : Urdu

The problem of identification of clauses in natural language processing is to find away to identify the each type of clause, e.g., Dependent clause, independent clause. Clause identification plays very important role in preprocessing task for language processing activities. This paper reports about the Clause Identification proposed for various Languages like English, Malayalam, Bengali and Urdu. Various clause identification approaches like Hidden Markov Model (HMM), Support Vector Model (SVM), and Rule based approaches, Maximum Entropy (ME) and Conditional Random Field (CRF), Entropy Guided Transformation Learning (ETL), have been used for POS tagging.
Etiology of congestive heart failure at a tertiary care hospital

ABSTRACT Objective To determine the frequency of various etiological factors responsible for causing congestive heart failure (CHF) in a tertiary care hospital in Peshawar, Pakistan. Subjects and Methods This retrospective, observational, single center study was conducted in Department of Medicine, Khyber Teaching Hospital, Peshawar from October 2009 to May 2010 and included 100 patients of CHF. After history and clinical examination, a diagnosis of CHF was established according to Framingham criteria. All patients had a 12-leads electrocardiogram (ECG), echocardiogram and serial blood tests. Results Out of 100 patients, 60% were male and 40% female with mean age of 54 years. Ischemic heart disease (IHD) was present in 35% of patients, hypertension in 27%, rheumatic heart disease (RHD) in 13%, cardiomyopathies in 11% and congenital heart disease in 6%. Conclusion IHD, hypertension, valvular heart disease and cardiomyopathy were the major causes of CHF in our patients. (Rawal Med J 2010;35: ). Key words: Electrocardiogram, echocardiogram, congestive cardiac failure. INTRODUCTION Congestive heart failure (CHF) is a condition that impairs the ability of the heart to fill with or pump a sufficient amount of blood through the body.1 More than 550,000 patients are diagnosed with CHF for the first time each year in US.2 The prevalence of CHF is known to rise with increasing age and affects about 10% of the population older than 75 years of age.3,4 According to Framingham study, major criteria are paroxysmal nocturnal dyspnea, orthopnea, raised jugular venous pulse, lung crepitations, cardiomegaly and gallop sounds. Minor criteria were ankle edema, night cough, dyspnea on exertion, hepatomegaly, pleural effusion and tachycardia.5 The diagnosis of predominantly systolic CHF required a minimum of two major or one major plus two minor criteria and LVEF
BOUNDARY OPTIMIZATION OF GROUND GLASS OPACITY IN CT IMAGES OF LUNG CANCER

In computer aided diagnosis, pre-processing, segmentation, feature extraction and classification are the steps involved. For segmentation the boundary must be defined to get regional information inside the boundary. Ground Glass Opacity (GGO) has ill-defined boundary. Hence, there is a necessity to optimize the boundary of GGO. Once the boundary is optimized, feature extraction and classification of malignant and benign of the particular GGO becomes easy. Using Distance Regularized Level Set Evolution (DRLSE) and Active contour without edges independently, the contour is grown and compared with the model image. The model image was created using the expertise of a Radiologist, applying Mattes Mutual information method. The contour which gives maximum mutual information is concluded as the optimized boundary. Wavelet transform has already been proven its application in identifying pits and cracks of corrosion metals. The same analogy is applied in GGO so that the partly solid and liquid GGOs can be precisely classified as malignant or benign. After optimizing the ill-defined boundary of GGO features of wavelet transformation were extracted along with textural features of mean and variance. Skewness and kurtosis were neglected since they were negligibly small. It is shown that on comparing the growing contour with model image using mattes mutual information, the DRLSE method shows greater results, without leaking compared to Active contour without edges. After extraction of features from wavelet transformation and textural features classification as malignant and benign was done using learning vector quantization (LVQ). On finding the optimized boundary, it is easier to classify the ground glass opacity as diffuse finding or local finding. Hence taking two images where one is taken as malignant and other as benign classification was done as benign and benign by the classifier. The malignant have been identified as benign due to minimum number of images used in training.
Working paper 2018 nr 1 Migration and the growth of low-wage work in the EU

Our paper is focusing on the current trends of migration and job polarization. In doing so, we have looked at the role of both the EU-enlargement and the refugee migration in an effort to trace the factors behind the growth of low-paying occupations in Europe. Our empirical findings however indicate that the growing share of migrant workers only has a limited general impact on the growth of the low-wage sector in the EU during the last two decades. The main drivers behind the increasing labour market polarization and growth of the lowwage sector in particular seem more related to technological changes and globalization. When considering the structure of immigrant workers and institutional settings, the impact of immigration workers on the expanding low-wage sector however differs. Most apparent is the positive impact of refugee migrants on the expanding low-wage sector in the AngloSaxon economies, and the negative, if any, impact in the other EU15 macro regions.
Multi-objective Decision Making Model for Construction Dispute Mediation

The construction industry is regarded as one of the most adversarial industries. Mediation as one of the alternative dispute resolution methods has gained acceptance in Hong Kong since its introduction in the 1980s. Mediation is a problem-solving process assisted by a neutral third-party, who tries to help the disputing parties in reaching an agreement. The study of mediation has focused on the identification of successful factors, disputants‘ satisfaction, mediation outcomes and tactics. In recent social research, mediation is defined as ̳administration and enforcement of rules or social norms‘ for disputants‘ conformity. Very little is known, however, about relationship between people‘s conformity to social norms for dispute resolution and their actual attitude. This paper reports a study that aims to bridge the gap, by examining what people should do in the mediation. Identifying efficient frontier is found to be the common goal in studies of negotiation analysis, game theory and decision making analysis. In this regard a multiple objective decision making system is employed to propose approximate efficiency frontier which can be used to engender an efficient and fair mediation agreement. The results obtained facilitated the investigation of the optimal solution and the trade-off process between parties.
Isolation , Identification and Detection of Some Virulence Factors of Staphylococci in milk and cheese in Baghdad

During 2011; 300 milk and white cheese samples were collected from Baghdad markets. Out of 200 staphylococcal isolates isolated from milk and white cheese samples, the predominant species was Staphylococcus aureus 97 isolates (48%), followed by S.chromogenes 82 (41%) and 21 (11%) S.epidermidis isolates. S. aureus isolates were DNase, coagulase, protease, urease, lipase, gelatinase and slime layer producers, other species were variable in the production of such virulence factors. S. chromogenes was the most prevalent isolated staphylococcal species from milk samples; while cheese samples contaminated mainly by S. aureus. Keyword: Staphylococci, Identification, Virulence factors, Slime layer production,
Utilizing Box-Jenkins methodology to forecast intermittent demand ( Full Paper Submission )

Intermittent demand presents difficulties in forecasting. A common situation is when a product demand shifts from normal demand to intermittent demand. In these conditions, it is not clear if Croston’s method (1972) provides advantages over single exponential smoothing (SES) or BoxJenkins methodologies. This paper will conduct simulations to investigate these situations. SES with a constant smoothing constant, SES with an alpha determined each period by an ARIMA model, Croston’s method with a constant alpha and Croston’s method with an alpha determined by an ARIMA model will be used to determine forecasts in many demand situations.
The Role of Non-financial Features in Business Crisis Prediction

Recent outbreak of corporate financial crises worldwide has brought attention to the need for a new international financial architecture which rests on crisis prediction and crisis management. It is therefore both desirable and vital to explore new predictive techniques for providing early warnings for predicting bankruptcy. Financial data have been widely used by researchers to predict business crisis, but few studies exploit the use of non-financial indicators in corporate governance to construct business crisis prediction model. This article introduces a prediction model based on a relatively new machine learning technique, support vector machines (SVM) for the field of business crisis prediction. The experiment results show that the combined use of both financial and non-financial features with SVM model leads to a more accurate prediction of financial distress.
Audiovisual speech processing and listening effort in untreated age-related hearing loss : evidence from functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) enables objective measurement of central auditory processing. We used fMRI to investigate neural processing of audiovisual speech in hearing impaired unaided and non-hearing impaired elderly subjects. Speech stimuli were used under four different conditions, visual only, auditory only and two audio-visual conditions, in which subjects could see the speakers face, one with congruent auditory and visual information and a second with incongruent information. While performance in this task did not differ between hearing impaired and non -hearing impaired participants, task-related neural activity differed. Hearing impaired participants showed higher neural activity in medial and lateral prefrontal cortex which correlated with the amount of high-frequency hearing loss. We suggest that the additional recruitment of frontal brain regions may relate to increased effort, which was supported by reports of increased daily listening effort in the hearing impaired group. An additional data analysis on resting state fMRI data in the same group of subjects, showed that this increased listening effort relates to decreased functional connectivity between inferior frontal and auditory cortex. Task and resting state fMRI data therefore provide valuable measures of central auditory processing of speech and increases in listening effort in the hearing impaired.