Miracle-dz/UniFAR-FTUs huggingface dataset:
Technical Efficiency and its Determinates in Cotton Production: A Case Study of Tehsil Pirmahal

Efficiency and determinants of cotton production in Pakistan. Data were collected from cotton farms through a well-structured questionnaire. To this end, different villages were randomly selected from all over Pakistan, and data on cotton crops were randomly selected from 299 respondents. To measure and estimate the technical efficiency of cotton growers, we applied Data Envelopment Analysis (DEA). In addition, we used Tobit regression analysis to determine the impact of technical efficiency determinants on cotton production. Our results show that the age of the peasants, the number of workers and the sales price of the farmers have a significant impact on the yield of cotton, while the method of sowing has a negative impact on the productivity of cotton. The study shows that the government should provide more available inputs at a lower price, while the cotton market should be reasonably priced. This research will help improve the living standards of agricultural communities and help increase investment in the agricultural sector.
The University of Northern Colorado Cancer Rehabilitation Institute Treadmill Protocol Accurately Measures VO2peak in Cancer Survivors

Utilizing protocols to obtain peak oxygen consumption (VO2peak) that were designed for the apparently health population may be inappropriate for cancer survivors (CS). The University of Northern Colorado Cancer Rehabilitation Institute (UNCCRI) has developed a treadmill protocol designed for CS to address this issue. Objective: To assess the construct validity of VO2 peak prediction equations for the UNCCRI multistage treadmill protocol against obtained VO2peak values in a population of CS. Methods: Forty-five CS completed the UNCCRI VO2peak treadmill protocol utilizing gas analysis (GAS) to obtain a true VO2peak value. A VO2peak value was also estimated from the gas analysis test (EstGAS) using American College of Sports Medicine’s (ACSM) prediction equations. Additionally, a separate UNCCRI treadmill protocol not using gas analysis (NoGAS) was conducted using ACSM VO2 prediction equations to determine VO2peak. An ANOVA was used to compare GAS, EstGAS, and NoGAS to assess the validity of the prediction equations versus the VO2peak obtained from gas analysis. A paired t-test was utilized to compare treadmill times between GAS and NoGAS to assess differences attributed to the use of gas analysis. A Pearson correlation was used to analyze the relationship between GAS and EstGAS VO2 peak values. Results: VO2 peak (mL•kg-1•min-1) did not significantly differ between GAS (26.8+7.0), EstGAS (26.2+6.5), and NoGAS (27.1+6.5) (P=0.2). Total treadmill time (min) differed significantly between GAS (12.1+2.8) and NoGAS (12.6+3.0; P<0.05). A significant, strong positive correlation was observed in VO2peak values between GAS and EstGAS (r=0.9; P<0.001). Conclusion: The UNCCRI treadmill protocol accurately predicts VO2peak when using gas analysis and when used with ACSM’s prediction equations demonstrating its construct validity. The UNCCRI treadmill protocol offers a safe and alternative measure of VO2peak for the cancer population.
Reconfigurable Monopole Antenna for WLAN / Bluetooth / ISM / GPS / LTE Applications

The paper presents a triple band reconfigurable antenna is designed for various wireless applications. The BAR 64-02 V PIN diode is used for attaining the reconfigurability of antenna. The antenna is compact in size and can be applicable for WLAN/ Bluetooth/ ISM/GPS/ GLONASS/GALILEO (2.4-2.48GHz) and LTE42/43 (3.4-3.8GHz) applications. This antenna is reconfigurable up to three frequency bands ranging 2 GHz to 5 GHz and simulated using ANSYS HFSS software and fabricated on a FR-4 epoxy substrate with 30×30 mm2 dimensions. The proposed antenna operates in the frequency range of 2.4 to 2.52 GHz, 3.06 to 3.13 GHz, 3.37 to 3.71 GHz when diode is ON state and the antenna operates in the range of 2.44 to 2.5 GHz, 3.17 to 3.29 GHz, 3.71 to 3.99 GHz when diode is OFF state.
Windowed Based Design of Quadrature Mirror Filter

In this paper, a windowed based design of Quadrature mirror filter is presented. In the flexible systems, to identify the frequencies of disturbances filter banks and quadrature mirror filter are employed. In this paper, a common approach to construct such filter-banks is to employ a two channel quadrature mirror filter (QMF) bank with FIR analysis and synthesis filters. High order Filters are required to achieve a sharp transition band and a high stop band attenuation, which results in a high computational complexity and a high system delay. QMF is designed using different widow techniques and find out the reconstruction Error and mean square Error and compare them. By comparing the results we conclude that Designing QMF with Blackman window has least Peak reconstruction error and with rectangular window has maximum PRE. The design examples illustrate that the proposed algorithm is superior in term of peak reconstruction error, computation time, and number of iterations. The proposed algorithm is simple, easy to implement, and linear in nature.
High Speed RNS-To-Binary Converter Design Using Parallel Prefix Adders

: In this paper, the implementation of residue number system reverse converters based on hybrid parallel-prefix adders is analyzed. The parallel prefix adder provides high speed and reduced delay arithmetic operations but it is not widely used since it suffers from high power consumption. Hence, a hybrid parallel prefix adder component is presented to perform fast modulo addition in Residue Number System reverse conversion. The proposed components are not only results in fast arithmetic operation and it also highly reduced the hardware complexity since it requires fewer amount of logic elements. In this work, the proposed components are implemented in different moduli sets reverse converter designs and the performances are compared for different values of n
Corn Silk- A Medicinal Boon

Herbs are one of humanity’s oldest known health care therapeutic essentials for a sustainable health, which forms the basic platform of modern medicines. Through out the world, there is now an inclination and search for stable diets with added value. One such important herb which is found extensively all over the world is corn silk. It is scientifically referred to as Maydis stigma or Zea as they reflect the soft, fiber-like growth that accompanies the ear of the corn. Corn silk is an essential herb that is used traditionally to treat a wide range of diseases. Its potential use is very much related to its properties and mechanism of action of its plant’s bioactive constituents such as flavonoids, terpenoids, etc. Pharmacological studies have proved that this traditional herb was found to have medicinal properties like anti-oxidant, antidepressant, anti-hyperlidemic, anti-diabetic,anti-inflammatory,neuroprotective toxicity and many more properties.
to IOT

: The phrase Internet of Things (IoT) refers to connecting various physical devices and objects throughout the world via internet. The term IoT was firstly proposed by Kevin Ashton in 1999.The following section illustrates basics of IoT. It deals with various layers used in IoT and some basic terms related to it. It is basically expansion of services provided by Internet. This section also presents the architecture of IoT. For example, when the household devices of our daily life connect with the internet the system can be called a Smart-Home in IoT environment. The IoT is not just deep vision for future. It is already under implementation and is having an impact on more than just technological development.
A SURVEY OF EXTRACTIVE SUMMARIZATION APPROACHES USING GRAPH MODEL

: With the rapid growth of internet also there is increase in on-line text document. Accessing such huge number of electronic textual documents creates challenge in front of user. It requires user to analyze the searched results one by one until satisfied information is acquired, which is time consuming process. Summary of document helps user to know about the page is about what? There are different approaches of summarization present. In this paper Web page summarization and Graph based summarization approaches are discussed. Web page summarization generate summary of web page based on the structure of web page. Graph based summarization models represent document with minimum loss of information and allows both the structure and content of document to be represented. The result of different graph based summarization models and analysis are presented in this paper. It shows that it is possible to boost summarization performance by building a better graph using richer features.
PREDICTING A FAST-TRACK MARITIME CAREER: CHARACTERISTICS OF SUCCESSFUL OFFICERS DURING TEENAGE YEARS

Fast-track maritime career is a topical question worldwide due to the shortage of seafarers in maritime industry. Assuming that the fast-track career officers’ relevant common characteristics in adolescence could predict future maritime career speed, the research questions of this research are: What were the common characteristics of fast-track career officers when they were 16-18? Were there any statistically significant differences between the fast-track career groups and the officers with a slower career at that age? A questionnaire survey involving 175 maritime officers was conducted in Latvia in January – October 2016, regarding officers’ family context, school achievement, involvement in sports, and personality traits when they were 16-18. Fast-track career officers perceived themselves as more conscientious, calm and more leadership oriented than the whole group in adolescence. Statistically significant differences among career-speed groups were found regarding family socioeconomic status, family atmosphere and family career support at that age. Based on those communalities among maritime officers with a fast-track carrier when they were 16-18, maritime education and training institutions could better find and give appropriate career guidance to prospective maritime officers. Even if maritime career speed is a very individualized phenomenon, family characteristics could be studied further as a potential good predictor of fast-track maritime career.
A NOVEL STUDY FOR SUMMARY/ATTRIBUTE BASED BUG TRACKING CLASSIFICATION USING LATENT SEMANTIC INDEXING AND SVD IN DATA MINING

This paper presentsa Latent Semantic Indexing (LSI) method for learningBug tracking concepts in document data. Each attribute in a vector provides the mark of participation of the document in data or term in the parallel concept . The objective to describe the concepts summary based, but to be capable to signify the documents and relations in a combined way for showing document-similarity, document-term, and term-term similarities or semantic relationship.Many technique for the implementing our research i.e. NLP, STEMMING, LUD, &SVD to the relevant similarity like bug report bug title, report summary etc., sinceevery bug report, and mined developer’s name who fixed the bug reports from the developers activity data. We processed the mined textual data, and got the term-to-document matrix. Our proposed model different machine learning methods for on the basis of summary and attribute based classification of bug reports which produce the outlier bugs from large amount of data that improved accuracy and efficiency bug classification and relevant base bug indexing which is similar in meaning by using LSI and SVD Technique.
EVALUATION OF ANTI-INFLAMMATORY, ANTIOXIDANT AND ANTI-PROLIFERATIVE ACTIVITIES OF HALOGENATED CHALCONES

Inflammation is one of the most important mechanisms of host defense as it marshals the attack on the injurious agent and leads to repair of the affected tissue. The four cardinal signs of inflammation are rubor (Redness) tumor (swelling), calor (heat) and dolor (pain). Inflammatory reactions underlie common chronic diseases, such as Rheumatoid arthritis, Lung fibrosis, many other autoimmune diseases like Ankylosing spondylitis, Crohn’s disease, Grave’s disease, Fibromyalgia. The Reactive oxygen species (ROS) as well as reactive nitrogen species (RNS) that result from the cellular redox process, at high concentrations they generate oxidative stress, deleterious process that can damage all cell structure. Antioxidants are the first line of defense against free radical damage, and are critical for maintaining optimum health. In both extrinsic pathway, and intrinsic pathway inflammatory conditions facilitate cancer development. Thus, Cancer Related Inflammation (CRI) is a key component of tumors and may represent the seventh hallmark of cancer. Chalcones (trans-1, 3-diaryl-2-propen-1-ones), a biosynthetic product of the shikimate pathway, and their derivatives are polyphenolic compounds of the flavonoid family. Chemically they consist of open-chain flavonoids in which two aromatic rings are joined by a three carbon alpha and beta unsaturated carbonyl system. Many naturally occurring chalcones are poly hydroxylated in the aryl rings. Changes in their structure have offered a high degree of diversity that has proven useful for the development of new medicinal agents having improved potency and lesser toxicity and good pharmacological actions.
Efficient Extraction of User Specific Sequential Data Patterns on Streaming Documents using Single-Sign on

: Textual records made and conveyed on the Internet are regularly changing in different structures. The vast majority of existing works are committed to point demonstrating and the development of individual themes, while consecutive relations of subjects in progressive reports distributed by a particular client are overlooked. In this paper, so as to describe and recognize customi zed and strange practices of Internet clients, we propose Sequential Topic Patterns (STPs) and define the issue of mining User-mindful Rare Sequential Topic Patterns (URSTPs) in archive streams on the Internet. They are uncommon overall yet moderately visit for particular clients, so can be connected in some genuine situations, for example, ongoing observing on anomalous client practices. We exhibit a gathering of calculations to understand this imaginative mining issue through three stages: pre-processing to extricate probabilistic points and distinguish sessions for various clients, producing all the STP applicants with (expected) bolster values for every client by example development, and choosing URSTPs by making client mindful irregularity investigation on inferred STPs. Investigates both genuine (Twitter) and manufactured datasets demonstrate that our approach can to be sure find exceptional clients and interpretable URSTPs adequately and productively, which altogether mirror clients' attributes. Textual file archives made and appropriated on the Internet are steadily changing in different structures. In this paper, with a specific end goal describe and distinguish cust omized and anomalous practices of Internet clients, we propose Sequential Topic Patterns (STPs) and plan the issue of mining User-mindful Rare Sequential Topic Patterns (URSTPs) in record streams on the Internet. They are uncommon all in all however generally visit fo r particular clients, so can be connected in some genuine situations, for example, constant observing on strange client practices. We exhibit a gathering of calculations to illuminate this inventive mining issue through three stages: preprocessing to extricat e probabilistic themes and distinguish sessions for various clients, producing all the STP competitors with (expected) bolster values for every client by example development, and choosing URSTPs by making client mindful irregularity investigation on inferred STPs . Probes both genuine (Twitter) and engineered datasets demonstrate that our approach can for sure find uncommon clients and interpretable URSTPs viably and productively, which essentially mirror clients ‘attributes.
Gene mutations distinguishing gastric from colorectal and esophageal adenocarcinomas.

Background Genetic analysis of gastrointestinal malignancies shows a great number of mutations. Most mutations found in gastric tumors are also found in colorectal and esophageal tumors. The challenge remains to identify mutations that distinguish gastric from colorectal and esophageal cancers. Using open-access cancer genomics data, we sought to identify mutations that accounted for the unique phenotypic features of gastric tumors. Methods Thirteen cancer genomics datasets with demographic, clinical, and genetic variables were analyzed. Pathologic stage and histology were compared between subjects with and without a specific mutated gene using two-sample t-tests, adjusted for multiple gene testing. Sequence convergence and functional impact of genetic mutations were analyzed using permutation test and PolyPhen-2 score. Results Analysis included 1,915 subjects with valid pathologic stage and histology. Mean age was 68 years (SD =10). About 54% were female. The most common race was Caucasian (37%) while minorities were rare with high rates of missing data (44%). Pathologic stage: 20% stage I, 35% stage II, 31% stage III, and 14% stage IV. Anatomical location: 30% gastric, 59% colorectal, and 11% esophageal. Histology of gastric cancer: 61% intestinal, 23% diffuse, 15% mixed, and 1% missing. Two mutated genes-CDH1, RHOA-distinguished gastric from colorectal and esophageal tumors. These mutations were highly specific to diffuse histology and advanced stages of gastric tumors and recurrent in transcribed regions known to impact protein functions. Conclusions CDH1 and RHOA regulate cell-cell adhesion which is vital to cell growth and proliferation. Identification of these potential driver mutations is critical to better define therapeutic vulnerabilities for the rational design of gastric cancer therapies.
Automatic Ship Detection For Pre-Annotated Ship Dataset Using Residual Neural Network

: Automatic object detection in the maritime environment has become very important, with a wide array of applications in areas such as naval warfare, vessel traffic services and fishery management. The manual detection of objects is not very efficient because of the tough climatic conditions such as fog, rain, storm etc. It may lead to faulty predictions and it is purely dependent on the expertise of the person. This contributes to the implementation of automatic object detection mechanism. In the system that exists, the detection and classification of ships are less than 90% in accuracy. The proposed system uses Residual Network architecture to identify the type of ship and annotate it with ship type labels such as accommodation ships, container ships, war ships and cruise ships with an accuracy greater than 90% and with less time consumption.
Congestion Aware Technique for multipath Load Balancing in MANET

: Mobile communication plays a vital role in disaster recovery management during emergency situations. It is helpful in situations where the system has less robust and less flexible infrastructure. Mobile Ad hoc Networks (MANET) are wireless networks comprise of a collection of mobile nodes with no fixed infrastructure. Due to their decentralized, self-configuring and dynamic nature, MANETs offer several advantages and are easy to install. However, the rapid growth in number and multiplicity of real-time network applications has made it imperative to consider the impact of end-to-end delay requirements of traffic on network. The research papers are published to increase the network performance on the network layer. In this paper, we propose a Reliable and Efficient Load balancing Technique based on AODV Protocol in Mobile Ad hoc Networks. In this protocol, a weight function based on route length, traffic load, energy level and freshness of each route is calculated and stored in the route cache. We propose a congestion aware multi-path routing protocol for load balancing in MANET. When the source node wants to forward the data packet to the destination, it uses the reactive route discovery technique where the multiple paths are well-known using multi-path Dijkstra algorithm. In this paper, by merging a multipath routing protocol with load balancing concept . One present a new protocol called CA-AODV. We use NS-2.34 to simulate the scenario. The simulation’s result shows the significant performance enhancement of the network for the multipath routing protocol with load balancing. The simulation results illustrate that the proposed load balanced routing protocol improves packet delivery ratio and reduces the delay.
Energy Efficient Query Optimization in Wireless Sensor Networks

– A wireless sensor network (WSN) is a wireless network consisting of distributed autonomous devices using sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations. A WSN Consists of ten to thousand of sensor nodes that communicate through wireless channels for information sharing and cooperative processing. In this our main focus is on base station energy-efficient queries optimization. Different from existing query optimization techniques that consider only query plans for extracting data from sensors at individual nodes, our approach takes into account both of the sensing and communication cost in query plans. When a new query is submitted to the base station, we check whether the new query can be evaluated using the result of currently running queries. If it is possible then we rewrites a new query using currently running queries at the base station without injecting it into the sensor network. Thus optimizing the query processing in Wireless Sensor Network. Simulation results show queries transmitted in merging, rewriting query plans and shows the query plan chosen in our approach consumes significantly less energy than an approach that optimizes on sensing cost only.
An Automated VM Security Framework for Live Migration

With the unbounded growth in the infrastructures for application hosting, demand from the consumers of the applications and the trade-off between the application availability with cost for application hosting is pushing the application providers towards cloud.The support from the cloud computing towards the application development are the dynamic load balancing, saving cost for energy and in premises hardware dependency. The dynamic load balancing is made possible by the concept of migrations of virtual machines or VMs. The migration includes identification of high loads on specific hosts, identification of possible virtual machines to be migrated and possible target hosts, where the VMs can be migrated. The challenge of migrating the virtual machines from the source to the destination physical hosts is during the migration process the virtual machines are exposed to the network and the other users available or have access to the same communication channels. Also, the virtual machines data to be made live in the target physical system, popularly called the VM images, are treated as regular files before those are live. Hence in the migration cycle, starting from the transfer of the virtual machine image and till the transferred virtual machine is live, there is a gap of security and which needs to be filled. The virtual machine images often contain the application, data generated by the application and data to be consumed by the application. Regardless to mention these three components are critical and must be prevented from the unauthorised access. Hence, a number of research attempts have proposed various schemes to secure the VM images by employing various encryption mechanisms. There methods are criticised for consuming high amount of computing capabilities for encrypting – decrypting VM images and resulting into violation of service level agreements by making the application not available for higher time.Thus, this work proposes a novel method for encrypting a higher volume VM image in less time by deploying a progressive and adaptive encryption method. The work also establishes the thought of the improvement by testing the algorithm in the light of SLA violation reduction compared with existing methods